-----Original Message-----

From: Carl Landwehr <carl.landwehr@gmail.com>

Sent: Tuesday, October 22, 2019 3:27 PM

To: privacyframework <privacyframework@nist.gov>

Subject: NIST Privacy Framework: Preliminary Draft Comments

I’ve made a few comments in the attach pdf version of the document. These comments come 

from a naive reader who has not been able to participate in the workshops and development of 

the drafts over the past year, so please acceot them in that light.

Regards,

—Carl Landwehr
Comment Identifier Comment

Comment 1 Line 5: Although there is certainly a 

logical structure in all that is presented 

below, I found it overall too abstract to 

be convincing. Perhaps this is my 

limitation since I'm not involved in 

day-to-day operations of an enterprise 

that would be likely to use this 

framework. I would strongly encourage 

development of several examples of 

how this framework might be used by 

different kinds of companies in 

different sectors (health, finance, social 

services, ..). Creating those examples 

will help readers like me and may also 

help the framework creators debug the 

framework. Perhaps this exercise has 

already been conducted, in which case 

i would encourage the publication of 

the results.

Comment 2 Line 82: individuals may not be able to 

understand the potential

Comment 3 Line 122: complex that individuals may 

not be able to understand the potential

Comment 4 Line 129: Here test text seems to be 

addressing privacy broadly construed, 

not just informational privacy. I think it 

would be better to restrict the 

discussion to informational privacy.
1

2

3

NIST PRIVACY FRAMEWORK: A TOOL FOR

IMPROVING PRIVACY THROUGH ENTERPRISE

RISK MANAGEMENT

September 6, 2019

PRELIMINARY DRAFT
NIST Privacy Framework Preliminary Draft September 6, 2019

1

4 Note to Reviewers

5 This preliminary draft is provided to promote the development of the NIST Privacy Framework: A Tool 

6 for Improving Privacy through Enterprise Risk Management (Privacy Framework). The National Institute 

7 of Standards and Technology (NIST) will use comments on this draft to develop version 1.0.

8 N.B. Throughout this document, references are made to a repository and a process for accepting 

9 external informative references. NIST will make this process and repository available with version 1.0. 

10 NIST welcomes feedback on this preliminary draft. In particular, NIST requests that reviewers consider 

11 the following questions: 

12 1. Does this preliminary draft:

13 a. adequately define outcomes that:

14 i. cover existing practices;

15 ii. strengthen individuals’ privacy protection;

16 iii. enable effective organizational use;

17 iv. support enterprise mission/business objectives; and

18 v. facilitate compliance with applicable laws or regulations;

19 b. appropriately integrate privacy risk into organizational risk;

20 c. provide guidance about privacy risk management practices at the right level of specificity;

21 d. adequately define the relationship between privacy and cybersecurity risk;

22 e. provide the capability for those in different organizational roles such as senior executives

23 and boards of directors, legal, compliance, security, and information technology or

24 operations to understand privacy risks and mitigations at the appropriate level of detail;

25 f. provide sufficient guidance and resources to aid organizations of all sizes to build and

26 maintain a privacy risk management program while maintaining flexibility; and

27 g. enable cost-effective implementation?

28 2. Will this preliminary draft, as presented:

29 a. be inclusive of, and not disruptive to, effective privacy practices in use today, including

30 widely used voluntary consensus standards that are not yet final;

31 b. enable organizations to use the Privacy Framework in conjunction with the Framework for

32 Improving Critical Infrastructure Cybersecurity to collaboratively address privacy and

33 cybersecurity risks; and

34 c. enable organizations to adapt to privacy risks arising from emerging technologies such as

35 the Internet of Things and artificial intelligence?

Comment 1
NIST Privacy Framework Preliminary Draft September 6, 2019

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36 Table of Contents

37 Note to Reviewers..............................................................................................................................1

38 Executive Summary............................................................................................................................3

39 Acknowledgements............................................................................................................................3

40 1.0 Privacy Framework Introduction ........................................................................................4

41 Overview of the Privacy Framework...................................................................................................... 5

42 Privacy Risk Management...................................................................................................................... 6

43 1.2.1 Cybersecurity and Privacy Risk Management................................................................................... 6

44 1.2.2 Relationship Between Privacy Risk Management and Risk Assessment .......................................... 7

45 Document Overview .............................................................................................................................. 8

46 2.0 Privacy Framework Basics ..................................................................................................9

47 Core ........................................................................................................................................................ 9

48 Profiles.................................................................................................................................................. 10

49 Implementation Tiers........................................................................................................................... 11

50 3.0 How to Use the Privacy Framework..................................................................................12

51 Mapping to Informative References.................................................................................................... 12

52 Strengthening Accountability............................................................................................................... 13

53 Establishing or Improving a Privacy Program ...................................................................................... 14

54 Applying to the System Development Life Cycle ................................................................................. 15

55 Using within the Data Processing Ecosystem ...................................................................................... 16

56 Informing Buying Decisions.................................................................................................................. 17

57 Appendix A: Privacy Framework Core ...............................................................................................18

58 Appendix B: Glossary .......................................................................................................................29

59 Appendix C: Acronyms......................................................................................................................32

60 Appendix D: Privacy Risk Management Practices ..............................................................................33

61 Appendix E: Implementation Tiers Definitions...................................................................................38

62 Appendix F: Roadmap ......................................................................................................................41

63 Appendix G: References....................................................................................................................42

64 List of Figures

65 Figure 1: Core, Profiles, and Implementation Tiers.............................................................................................5

66 Figure 2: Cybersecurity and Privacy Risk Relationship ........................................................................................6

67 Figure 3: Relationship Between Privacy Risk and Organizational Risk .................................................................7

68 Figure 4: Privacy Framework Core Structure......................................................................................................9

69 Figure 5: Profile Development Process............................................................................................................ 11

70 Figure 6: Notional Collaboration and Communication Flows Within an Organization ........................................ 13

71 Figure 7: Data Processing Ecosystem Relationships.......................................................................................... 16

72 Figure 8: Using Functions to Manage Privacy Risk............................................................................................ 19

73 List of Tables

74 Table 1: Privacy Framework Function and Category Unique Identifiers............................................................. 20

75 Table 2: Privacy Framework Core.................................................................................................................... 21

76 Table 3: Privacy Engineering and Security Objectives....................................................................................... 35

77
NIST Privacy Framework Preliminary Draft September 6, 2019

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78 Executive Summary

79 For more than two decades, the Internet and associated information technologies have driven 

80 unprecedented innovation, economic value, and improvement in social services. Many of these benefits 

81 are fueled by data about individuals that flow through a complex ecosystem—so complex that 

82 individuals may not be able to understand the potential consequences for their privacy as they interact 

83 with systems, products, and services. At the same time, organizations may not realize the full extent of 

84 these consequences for individuals, for society, or for their enterprises, which can affect their 

85 reputations, their bottom line, and their future prospects for growth.

86 The National Institute of Standards and Technology (NIST), working in collaboration with private and 

87 public stakeholders, has developed this voluntary NIST Privacy Framework: A Tool for Improving Privacy 

88 through Enterprise Risk Management (Privacy Framework). The Privacy Framework can drive better 

89 privacy engineering and help organizations protect individuals’ privacy by: 

90 • Building customer trust by supporting ethical decision-making in product and service design or

91 deployment that optimizes beneficial uses of data while minimizing adverse consequences for

92 individuals’ privacy and society as a whole;

93 • Fulfilling current compliance obligations, as well as future-proofing products and services to

94 meet these obligations in a changing technological and policy environment; and

95 • Facilitating communication about privacy practices with customers, assessors, and regulators.

96 Deriving benefits from data while simultaneously managing risks to individuals’ privacy is not well-suited 

97 to one-size-fits-all solutions. Like building a house, where homeowners get to choose room layouts but 

98 need to trust that the foundation is well-engineered, privacy protection should allow for individual 

99 choices, as long as effective privacy risk mitigations are already engineered into products and services. 

100 The Privacy Framework—through a risk- and outcome-based approach—is flexible enough to address 

101 diverse privacy needs, enable more innovative and effective solutions that can lead to better outcomes 

102 for individuals and enterprises, and stay current with technology trends, including artificial intelligence 

103 and the Internet of Things. 

104 The Privacy Framework follows the structure of the Framework for Improving Critical Infrastructure 

105 Cybersecurity (Cybersecurity Framework) [1] to facilitate the use of both frameworks together. Like the 

106 Cybersecurity Framework, the Privacy Framework is composed of three parts: the Core, Profiles, and 

107 Implementation Tiers. Each component reinforces privacy risk management through the connection 

108 between business and mission drivers and privacy protection activities. 

109 • The Core enables a dialogue—from the executive level to the implementation/operations

110 level—about important privacy protection activities and desired outcomes.

111 • Profiles enable the prioritization of the outcomes and activities that best meet organizational

112 privacy values, mission/business needs, and risks.

113 • Implementation Tiers support decision-making and communication about the sufficiency of

114 organizational processes and resources to manage privacy risk.

115 In summary, the Privacy Framework is intended to help organizations build better privacy foundations 

116 by bringing privacy risk into parity with their broader enterprise risk portfolio.

117 Acknowledgements

118 Acknowledgements will be included in version 1.0.

Comment

2
NIST Privacy Framework Preliminary Draft September 6, 2019

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119 1.0 Privacy Framework Introduction

120 For more than two decades, the Internet and associated information technologies have driven 

121 unprecedented innovation, economic value, and access to social services. Many of these benefits are 

122 fueled by data about individuals that flow through a complex ecosystem—so complex that individuals

123 may not be able to understand the potential consequences for their privacy as they interact with 

124 systems, products, and services. Organizations may not fully realize the consequences either. Failure to 

125 manage privacy risks can have direct adverse consequences for people at both the individual and 

126 societal level, with follow-on effects on organizations’ reputation, bottom line, and future prospects for 

127 growth. Finding ways to continue to derive benefits from data while simultaneously protecting 

128 individuals’ privacy is challenging, and not well-suited to one-size-fits-all solutions.

129 Privacy is challenging because not only is it an all-encompassing concept that helps to safeguard 

130 important values such as human autonomy and dignity, but also the means for achieving it can vary. For 

131 example, privacy can be achieved through seclusion, limiting observation, or individuals’ control of 

facets of their identities (e.g., body, data, reputation). 132 1 Moreover, human autonomy and dignity are not 

133 fixed, quantifiable constructs; they are filtered through cultural diversity and individual differences. This

134 broad and shifting nature of privacy makes it difficult to communicate clearly about privacy risks within 

135 and between organizations and with individuals. What has been missing is a common language and 

136 practical tool that is flexible enough to address diverse privacy needs. 

137 The National Institute of Standards and Technology (NIST) has developed this voluntary NIST Privacy 

138 Framework: A Tool for Improving Privacy through Enterprise Risk Management (Privacy Framework) to 

139 help organizations manage privacy risks by:

140 • Taking privacy into account as they design and deploy systems, products, and services that

141 affect individuals;

142 • Integrating privacy practices into their business processes that result in effective solutions to

143 mitigate any adverse impacts; and

144 • Communicating about these practices.

145 The Privacy Framework is intended to be widely usable by organizations of all sizes and agnostic to any 

146 particular technology, sector, law, or jurisdiction. 

147 • Different parts of an organization’s workforce, including executives, legal, and information

148 technology (IT) may take responsibility for different outcomes and activities.

149 • It encourages cross-organization collaboration to develop Profiles and achieve outcomes.

150 • The Privacy Framework is usable by any organization or entity regardless of its role in the data

151 processing ecosystem—the complex and interconnected relationships among entities involved

152 in creating or deploying systems, products, or services.

1 There are many publications that provide an in-depth treatment on the background of privacy or different 

aspects of the concept. For two examples, see Daniel Solove, Understanding Privacy, Harvard University Press, 

2010; and Evan Selinger and Woodrow Hartzog, “Obscurity and Privacy,” Routledge Companion to Philosophy of 

Technology, 2014, at https://ssrn.com/abstract=2439866.

Comment 

3

Comment 

4
NIST Privacy Framework Preliminary Draft September 6, 2019

5

153 Overview of the Privacy Framework 

154 As shown in Figure 1, the

155 Privacy Framework is composed 

156 of three parts: the Core, 

157 Profiles, and Implementation 

158 Tiers. Each component 

159 reinforces privacy risk 

160 management through the 

161 connection between 

162 business/mission drivers and 

163 privacy protection activities. As 

164 further explained in section 2:

165 • The Core is a set of

166 privacy protection 

167 activities and outcomes

168 that allows for 

169 communicating

170 prioritized privacy 

171 protection activities 

172 and outcomes across the 

173 organization from the executive level to the implementation/operations level. There are five 

174 Functions: Identify-P, Govern-P, Control-P, Communicate-P, and Protect-P. The first four can be 

175 used to manage privacy risks arising from data processing, while Protect-P can help 

organizations manage privacy risks associated with privacy breaches.

2 176 Protect-P is not the only 

177 way to manage privacy risks associated with privacy breaches. For example, organizations may 

178 use the Cybersecurity Framework Functions in conjunction with the Privacy Framework to 

179 collectively address privacy and cybersecurity risks. The Core is further divided into key 

180 Categories and Subcategories—which are discrete outcomes—for each Function.

181 • A Profile represents the organization’s current privacy activities or desired outcomes. To

182 develop a Profile, an organization can review all of the Functions, Categories, and Subcategories

183 to determine which are most important to focus on based on business/mission drivers, types of

184 data processing, and individuals’ privacy needs. The organization can create or add Functions,

185 Categories, and Subcategories as needed. Profiles can be used to identify opportunities for

186 improving privacy posture by comparing a “Current” Profile (the “as is” state) with a “Target”

187 Profile (the “to be” state). Profiles can be used to conduct self-assessments and to communicate

188 within an organization or between organizations about how privacy risks are being managed.

189 • Implementation Tiers (“Tiers”) provide a point of reference on how an organization views

190 privacy risk and whether it has sufficient processes and resources in place to manage that risk.

191 Tiers reflect a progression from informal, reactive responses to approaches that are agile and

192 risk informed. When selecting Tiers, an organization should consider its Target Profile and how

193 this relates to current risk management practices; its data processing systems, products, or

2 The “-P” at the end of each Function name indicates that it is from the Privacy Framework in order to avoid 

confusion with Cybersecurity Framework Functions.

The Core provides an increasingly granular 

set of activities and outcomes that enable 

an organizational dialogue about 

managing privacy risk

Profiles are a selection of 

specific Functions, 

Categories, and 

Subcategories from the 

Core that the organization 

has prioritized to help it 

manage privacy risk

CURRENT

TARGET

Implementation Tiers help an organization 

communicate about whether it has sufficient 

processes and resources in place to manage 

privacy risk and achieve its Target Profile

Figure 1: Core, Profiles, and Implementation Tiers
NIST Privacy Framework Preliminary Draft September 6, 2019

6

194 services; legal and regulatory requirements; business/mission objectives; organizational privacy 

195 values and individuals’ privacy needs; and organizational constraints.

196 Privacy Risk Management

197 While some organizations have a robust grasp of privacy risk management, a common understanding of 

many aspects of this topic is still not widespread.

3 198 To promote broader understanding, this section 

199 covers concepts and considerations that organizations may use to develop, improve, or communicate

200 about privacy risk management. Appendix D provides additional guidance on key privacy risk 

201 management practices.

202 1.2.1 Cybersecurity and Privacy Risk Management

203 Since its release in 2014, the 

204 Cybersecurity Framework has helped 

205 organizations to communicate and 

206 manage cybersecurity risk. [1] While 

207 managing cybersecurity risk 

208 contributes to managing privacy risk, it 

209 is not sufficient, as privacy risks can 

210 also arise outside the scope of 

211 cybersecurity risks. Figure 2 illustrates 

212 how NIST considers the overlap and 

213 differences between cybersecurity 

214 and privacy risks. 

215 The NIST approach to privacy risk is to consider potential problems individuals could experience arising 

216 from system, product, or service operations with data, whether in digital or non-digital form, through a 

217 complete life cycle from data collection through disposal. The Privacy Framework describes these data 

218 operations in the singular as a data action and collectively as data 

219 processing. The problems individuals can experience as a result of

220 data processing can be expressed in various ways, but NIST describes 

221 them as ranging from dignity-type effects such as embarrassment or

222 stigmas to more tangible harms such as discrimination, economic

loss, or physical harm.4 223 Problems can arise as unintended 

224 consequences from data processing that organizations conduct to 

225 meet their mission or business objectives. An example is the concerns 

226 that certain communities had about the installation of “smart 

227 meters” as part of the Smart Grid, a nationwide technological effort 

to increase energy efficiency.5 228 The ability of these meters to collect,

229 record, and distribute highly granular information about household 

230 electrical use could provide insight into people’s behavior inside their 

3 See Summary Analysis of the Responses to the NIST Privacy Framework Request for Information [2] at p. 7.

4 NIST has created an illustrative problem set for use in privacy risk assessment. See NIST Privacy Risk Assessment 

Methodology [3]. Other organizations may have created problem sets as well, or may refer to them as adverse 

consequences or harms.

5 See, for example, NIST Internal Report (IR) 7628 Revision 1 Volume 1, Guidelines for Smart Grid Cybersecurity: 

Volume 1 – Smart Grid Cybersecurity Strategy, Architecture, and High-Level Requirements at [4] p. 26.

Data Action

A system/product/service 

data life cycle operation, 

including, but not limited 

to collection, retention, 

logging, generation, 

transformation, use, 

disclosure, sharing, 

transmission, and disposal.

Data Processing

The collective set of data 

actions.

Cybersecurity 

Risks

Privacy 

Risks

associated with loss 

of confidentiality, 

integrity, or 

availability

privacy 

breach

associated with 

unintended 

consequences of 

data processing

Figure 2: Cybersecurity and Privacy Risk Relationship
NIST Privacy Framework Preliminary Draft September 6, 2019

7

homes.6 231 The meters were operating as intended, but the data processing could lead to unintended 

232 consequences that people might feel surveilled.

233 However, these problems also can arise from privacy breaches where there is a loss of confidentiality, 

234 integrity, or availability at some point in the data processing, such as data theft by external attackers or 

235 the unauthorized access or use of data by employees who exceed their authorized privileges. Figure 2

236 shows privacy breach as the overlap between a loss of confidentiality, integrity, or availability and 

237 unintended consequences of data processing for mission or business objectives.

238 Once an organization can identify the likelihood of any given problem arising from the data processing, 

239 which the Privacy Framework refers to as a problematic data action, it can assess the impact should the 

240 problematic data action occur. This impact assessment is where privacy risk and organizational risk

241 intersect. Individuals, whether singly or in groups (including at a societal level) experience the direct 

242 impact of problems. As a result of the problems individuals experience, an organization may experience 

243 impacts such as noncompliance costs, customer abandonment of products and services, or harm to its 

244 external brand reputation or internal culture. These organizational impacts can be drivers for informed 

245 decision-making about resource allocation to strengthen privacy programs and to help organizations 

246 bring privacy risk into parity with other risks they are managing at the enterprise level. Figure 3

247 illustrates this relationship between privacy risk and organizational risk.

248 1.2.2 Relationship Between Privacy Risk Management and Risk Assessment

249 Privacy risk management is a cross-organizational set of processes that helps organizations to 

250 understand how their systems, products, and services may create problems for individuals and how to 

251 develop effective solutions to manage such risks. Privacy risk assessment is a sub-process for identifying, 

252 evaluating, prioritizing, and responding to specific privacy risks. In general, privacy risk assessments 

253 should produce the information that can help organizations to weigh the benefits of the data processing 

254 against the risks and to determine the appropriate response (see Appendix D for more guidance on the 

255 operational aspects of privacy risk assessment). Organizations may choose to respond to privacy risk in 

256 different ways, depending on the potential impact to individuals and resulting impacts to organizations. 

257 Approaches include:

258 • Mitigating the risk (e.g., organizations may be able to apply technical and/or policy measures to

259 the systems, products, or services that minimize the risk to an acceptable degree);

6 See NIST IR 8062, An Introduction to Privacy Engineering and Risk Management in Federal Systems at [5] p. 2. For 

additional types of privacy risks associated with unintended consequences of data processing, see Appendix E of 

NIST IR 8062.

Problem

arises from data 

processing

Individual

experiences direct impact 

(e.g., embarrassment, 

discrimination, economic 

loss)

Organization

resulting impact

(e.g., customer abandonment, 

noncompliance costs, harm to 

reputation or internal culture)

Figure 3: Relationship Between Privacy Risk and Organizational Risk
NIST Privacy Framework Preliminary Draft September 6, 2019

8

260 • Transferring or sharing the risk (e.g., contracts are a means of sharing or transferring risk to

261 other organizations, privacy notices and consent mechanisms are a means of sharing risk with

262 individuals);

263 • Avoiding the risk (e.g., organizations may determine that the risks outweigh the benefits, and

264 forego or terminate the data processing); or

265 • Accepting the risk (e.g., organizations may determine that problems for individuals are minimal

266 or unlikely to occur, therefore the benefits outweigh the risks, and it is not necessary to invest

267 resources in mitigation).

268 Privacy risk assessments are particularly important because, as noted above, privacy is a condition that 

269 safeguards multiple values. The methods for safeguarding these values may differ, and moreover, may 

270 be in tension with each other. For instance, if the organization is trying to achieve privacy by limiting 

271 observation, this may lead to implementing measures such as distributed data architectures or privacy272 enhancing cryptographic techniques that hide data even from the organization. If the organization is 

273 also trying to enable individual control, the measures could conflict. For example, if an individual 

274 requests access to data, the organization may not be able to produce the data if the data has been 

275 distributed or encrypted in ways the organization cannot access. Privacy risk assessments can help an 

276 organization understand in a given context the values to protect, the methods to employ, and the way

277 to balance implementation of different types of measures.

278 Lastly, privacy risk assessments help organizations distinguish between privacy risk and compliance risk.

279 Identifying if data processing could create problems for individuals, even when an organization may be 

280 fully compliant with applicable laws or regulations, can help with ethical decision-making in system, 

281 product, and service design or deployment. This facilitates optimizing beneficial uses of data while 

282 minimizing adverse consequences for individuals’ privacy and society as a whole, as well as avoiding

283 losses of trust that damage organizations’ reputations, slow adoption, or cause abandonment of

284 products and services. 

285 Document Overview

286 The remainder of this document contains the following sections and appendices:

287 • Section 2 describes the Privacy Framework components: the Core, Profiles, and Implementation

288 Tiers.

289 • Section 3 presents examples of how the Privacy Framework can be used.

290 • Appendix A presents the Privacy Framework Core in a tabular format: Functions, Categories, and

291 Subcategories.

292 • Appendix B contains a glossary of selected terms.

293 • Appendix C lists acronyms used in this document.

294 • Appendix D considers key practices that contribute to successful privacy risk management.

295 • Appendix E defines the Implementation Tiers.

296 • Appendix F provides a placeholder for a companion roadmap covering NIST’s next steps and

297 identifying key areas where the relevant practices are not well enough understood to enable

298 organizations to achieve a privacy outcome.

299 • Appendix G lists the references for this document.
NIST Privacy Framework Preliminary Draft September 6, 2019

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300 2.0 Privacy Framework Basics

301 The Privacy Framework provides a common language for understanding, managing, and communicating 

302 privacy risk with internal and external stakeholders. It can be used to help identify and prioritize actions 

303 for reducing privacy risk, and it is a tool for aligning policy, business, and technological approaches to 

304 managing that risk. Different types of entities—including sector-specific organizations—can use the 

305 Privacy Framework for different purposes, including the creation of common Profiles. 

306 Core

307 The Core provides a set of activities and 

308 outcomes that enable an organizational 

309 dialogue about managing privacy risk. The 

310 Core comprises three elements: 

311 Functions, Categories, and Subcategories, 

312 depicted in Figure 4.

313 The Core elements work together: 

314 • Functions organize foundational

315 privacy activities at their highest 

316 level. They aid an organization in

317 expressing its management of

318 privacy risk by understanding and managing data processing, enabling risk management

319 decisions, determining how to interact with individuals, and improving by learning from

320 previous activities. There are five Functions: Identify-P, Govern-P, Control-P, Communicate-P,

321 and Protect-P. The first four can be used to manage privacy risks arising from data processing,

while Protect-P can help organizations manage privacy risks associated with privacy breaches.7 322

323 Protect-P is not the only way to manage privacy risks associated with privacy breaches. For

324 example, organizations may use the Cybersecurity Framework Functions in conjunction with the

325 Privacy Framework to collectively address privacy and cybersecurity risks.

326 • Categories are the subdivisions of a Function into groups of privacy outcomes closely tied to

327 programmatic needs and particular activities. Examples include: “Disassociated Processing,”

328 “Inventory and Mapping,” and “Risk Assessment.”

329 • Subcategories further divide a Category into specific outcomes of technical and/or management

330 activities. They provide a set of results that, while not exhaustive, help support achievement of

331 the outcomes in each Category. Examples include: “Systems/products/services that process data

332 are inventoried,” “Data are processed to limit the identification of individuals (e.g., differential

333 privacy techniques, tokenization),” and “Data corrections or deletions can be communicated to

334 individuals or organizations (e.g., data sources) in the data processing ecosystem.”

335 The five Functions, defined below, are not intended to form a serial path or lead to a static desired end 

336 state. Rather, the Functions should be performed concurrently and continuously to form or enhance an 

337 operational culture that addresses the dynamic nature of privacy risk. See Appendix A for the complete 

338 Core. 

7 The “-P” at the end of each Function name indicates that it is from the Privacy Framework in order to avoid 

confusion with Cybersecurity Framework Functions.

Figure 4: Privacy Framework Core Structure

FUNCTIONS CATEGORIES SUBCATEGORIES

Identify-P

Govern-P

Protect-P

Control-P

Communicate-P
NIST Privacy Framework Preliminary Draft September 6, 2019

10

339 • Identify-P – Develop the organizational understanding to manage privacy risk for individuals

340 arising from data processing.

341 The activities in the Identify-P Function are foundational for effective use of the Privacy

342 Framework. Inventorying the circumstances under which data are processed, understanding the

343 privacy interests of individuals directly or indirectly served or affected by the organization, and

344 conducting risk assessments enable an organization to understand the business environment in

345 which it is operating and identify and prioritize privacy risks. Examples of Categories include:

346 “Inventory and Mapping,” “Business Environment,” and “Risk Assessment.”

347 • Govern-P – Develop and implement the organizational governance structure to enable an

348 ongoing understanding of the organization’s risk management priorities that are informed by

349 privacy risk.

350 The Govern-P Function is similarly foundational, but focuses on organizational-level activities

351 such as establishing organizational privacy values and policies, identifying legal/regulatory

352 requirements, and understanding organizational risk tolerance that enable an organization to

353 focus and prioritize its efforts, consistent with its risk management strategy and business needs.

354 Examples of Categories include: “Governance Policies, Processes, and Procedures,” “Risk

355 Management Strategy,” and “Monitoring and Review.”

356 • Control-P – Develop and implement appropriate activities to enable organizations or individuals

357 to manage data with sufficient granularity to manage privacy risks.

358 The Control-P Function considers data management from both the standpoint of the

359 organization and the individual. Examples of Categories include: “Data Management Policies,

360 Processes, and Procedures” and “Data Management.”

361 • Communicate-P – Develop and implement appropriate activities to enable organizations and

362 individuals to have a reliable understanding about how data are processed and associated

363 privacy risks.

364 The Communicate-P Function recognizes that both organizations and individuals need to know

365 how data are processed in order to manage privacy risk effectively. Examples of Categories

366 include: “Communication Policies, Processes, and Procedures” and “Data Processing

367 Awareness.”

368 • Protect-P – Develop and implement appropriate data processing safeguards.

369 The Protect-P Function covers data protection to prevent privacy breaches, the overlap between

370 privacy and cybersecurity risk management. Examples of Categories include: “Identity

371 Management, Authentication, and Access Control,” “Data Security,” and “Protective

372 Technology.”

373 Profiles

374 Profiles are a selection of specific Functions, Categories, and Subcategories from the Core that the 

375 organization has prioritized to help it manage privacy risk. Profiles align the Functions, Categories, and 

376 Subcategories with the business requirements, risk tolerance, privacy values, and resources of the 

377 organization. Under the Privacy Framework’s risk-based approach, organizations may not need to 

378 achieve every outcome or activity reflected in the Core. When developing a Profile, an organization may 

379 select or tailor the Privacy Framework’s Functions, Categories, and Subcategories to its specific needs. 

380 An organization or industry sector also may develop its own additional Functions, Categories, and 
NIST Privacy Framework Preliminary Draft September 6, 2019

11

381 Subcategories to account for unique organizational risks. An organization determines these needs by 

382 considering organizational or industry sector goals, legal/regulatory requirements and industry best 

383 practices, the organization’s risk management priorities, and the privacy needs of individuals who are 

384 part of—or directly or indirectly served or affected by—an organization’s systems, products, or services. 

385 Profiles can be used to describe the current state or the desired target state of specific privacy activities. 

386 As Figure 5 reflects, a Current Profile indicates privacy outcomes that an organization is currently 

387 achieving, while a Target Profile indicates the outcomes needed to achieve the desired privacy risk 

388 management goals. The differences between the two Profiles enable an organization to identify gaps, 

389 develop an action plan for improvement, and gauge the resources that would be needed (e.g., staffing, 

390 funding) to achieve privacy goals. This forms the basis of an organization’s plan for reducing privacy risk 

391 in a cost-effective, prioritized manner. Profiles also can aid in communicating risk within and between 

392 organizations by helping organizations understand and compare the current or desired state of privacy

393 outcomes. 

394 This Privacy Framework does not prescribe Profile templates to allow for flexibility in implementation. 

395 An organization may choose to have multiple Profiles for specific organizational components, systems, 

396 products, or services, or categories of individuals (e.g., employees, customers).

397 Implementation Tiers

398 Tiers support organizational decision-making about how to manage privacy risk by taking into account 

399 the nature of the privacy risks engendered by the organization’s systems, products, or services and the 

400 sufficiency of the processes and resources the organization has in place to manage such risks. When 

401 selecting Tiers, an organization should consider its current risk management practices; its data 

402 processing systems, products, or services; legal and regulatory requirements; business/mission 

403 objectives; organizational privacy values and individuals’ privacy needs; and organizational constraints.

404 There are four distinct tiers: Partial (Tier 1), Risk Informed (Tier 2), Repeatable (Tier 3), and Adaptive 

405 (Tier 4). Tiers do not represent maturity levels, although organizations identified as Tier 1 are 

406 encouraged to consider moving toward Tier 2. Some organizations may never need to achieve Tier 3 or 4 

407 or may only focus on certain areas of these tiers. Progression to higher Tiers is appropriate when an 

408 organization’s processes or resources at its current Tier are insufficient to help it manage its privacy 

409 risks. 

410 An organization can use the Tiers to communicate with stakeholders whether it has sufficient resources 

411 and processes in place to achieve its Target Profile. This should influence the prioritization of elements 

412 included in a Target Profile, and should influence assessments of progress in addressing gaps. The 

413 definitions of the Tiers are set forth in Appendix E.

Figure 5: Profile Development Process

CORE CURRENT PROFILE

Identify-P

Govern-P

Protect-P

Control-P

Communicate-P

TARGET PROFILE

Identify-P

Govern-P

Protect-P

Identify-P

Govern-P

Protect-P

Control-P

Communicate-P
NIST Privacy Framework Preliminary Draft September 6, 2019

12

414 3.0 How to Use the Privacy Framework

415 When used as a risk management tool, the Privacy Framework can assist an organization in its efforts to 

416 optimize beneficial uses of data and the development of innovative systems, products, and services 

417 while minimizing adverse consequences for individuals. The Privacy Framework can help organizations

418 answer the fundamental question, “How are we considering the impacts to individuals as we develop 

419 our systems, products, and services?” As a result, the Privacy Framework can serve as the foundation for 

420 a new privacy program or a mechanism for improving an existing program. In either case, it is designed 

421 to complement existing business and system development operations, to provide a means of expressing 

422 privacy requirements to business partners and customers, and to support the identification of gaps in an 

423 organization’s privacy practices. 

424 To account for the unique needs of an organization, there are a wide variety of ways to use the Privacy 

425 Framework. The decision about how to apply it is left to the implementing organization. For example, 

426 one organization may choose to use the Implementation Tiers to articulate its envisioned privacy risk 

427 management processes. Another organization may already have robust privacy risk management 

428 processes, but may use the Core’s five Functions to analyze and articulate any gaps. Alternatively, an 

429 organization seeking to establish a privacy program can use the Core’s Categories and Subcategories as a 

430 reference. The variety of ways in which the Privacy Framework can be used by organizations should 

431 discourage the notion of “compliance with the Privacy Framework” as a uniform or externally 

432 referenceable concept.

433 The following subsections present different ways in which organizations can use the Privacy Framework. 

434 Mapping to Informative References 

435 The Privacy Framework is technology neutral, but it supports technological innovation because any 

436 organization or industry sector can map the outcome-based Subcategories in the Core to standards, 

437 guidelines, and practices that evolve with technology and related business needs. By relying on 

438 consensus-based standards, guidelines, and practices, the tools and methods available to achieve 

439 positive privacy outcomes can scale across borders, accommodate the global nature of privacy risks, and 

440 evolve with technological advances and business requirements. The use of existing and emerging 

441 standards will enable economies of scale and drive the development of systems, products, and services 

442 that meet identified market needs while being mindful of the privacy needs of individuals. 

443 Mapping Subcategories to specific sections of standards, guidelines, and practices supports the 

444 achievement of the outcomes associated with each Subcategory. The Subcategories also can be used to 

445 identify where additional or revised standards, guidelines, and practices would help an organization to 

446 address emerging needs. An organization implementing a given Subcategory, or developing a new 

447 Subcategory, might discover that there are insufficient informative references for a related activity. To 

448 address that need, the organization might collaborate with technology leaders and/or standards bodies 

449 to draft, develop, and coordinate standards, guidelines, or practices.

450 NIST has developed a mapping of the Subcategories to relevant NIST guidance, as well as a process for 

451 organizations or industry sectors to submit additional informative references and mappings for 

452 publication on NIST’s website at https://www.nist.gov/privacy-framework. These resources can support 

453 organizations’ application of the Privacy Framework and achievement of better privacy practices.
NIST Privacy Framework Preliminary Draft September 6, 2019

13

454 Strengthening Accountability 

455 Accountability is generally considered a key privacy principle, although conceptually it is not unique to 

privacy.8 456 Accountability occurs throughout an organization, and it can be expressed at varying degrees 

457 of abstraction, for example as a cultural value, as governance policies and procedures, or as traceability 

458 relationships between privacy requirements and controls. Privacy risk management can be a means of 

459 supporting accountability at all organizational levels as it connects senior executives, who can

460 communicate the organization’s privacy values and risk tolerance, to those at the business/process 

461 manager level, who can collaborate on the development and implementation of governance policies and 

462 procedures that support the organizational privacy values. These policies and procedures can then be 

463 communicated to those at the implementation/operations level, who collaborate on defining the 

464 privacy requirements that support the expression of the policies and procedures in the organization’s 

465 systems, products, and services. Personnel at the implementation/operations level also select, 

466 implement, and assess controls as the technical and policy measures that meet the privacy 

467 requirements, and report upward on progress, gaps and deficiencies, and changing privacy risks so that 

468 those at the business/process manager level and the senior executives can better understand and 

469 respond appropriately. 

470 Figure 6 provides a graphical representation of this iterative cycle and how elements of the Privacy 

471 Framework can be incorporated to facilitate the process. In this way, organizations can use the Privacy 

8 See, e.g., Organisation for Economic Co-operation and Development (OECD), OECD Guidelines on the Protection 

of Privacy and Transborder Flows of Personal Data at 

https://www.oecd.org/internet/ieconomy/oecdguidelinesontheprotectionofprivacyandtransborderflowsofpersona

ldata.htm; International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC),

ISO/IEC 29100, Information technology – Security techniques – Privacy framework at 

https://standards.iso.org/ittf/PubliclyAvailableStandards/c045123_ISO_IEC_29100_2011.zip; Alliance of 

Automobile Manufacturers, Inc. and Association of Global Automakers, Inc., Consumer Privacy Protection 

Principles: Privacy Principles for Vehicle Technologies and Services at https://autoalliance.org/wpcontent/uploads/2017/01/Consumer_Privacy_Principlesfor_VehicleTechnologies_Services-03-21-19.pdf.

Business/Process Manager Level

Responsibilities

• Develop Profiles

• Allocate budget

• Inform Tier selection

Senior Executive Level

• Express mission priorities, risk

tolerance, organizational privacy

values, and budget

• Accept/decline risk decisions

Responsibilities

Implementation/Operations Level

• Implement Profiles

• Monitor progress

• Conduct privacy risk assessments

Responsibilities

C O L L A B O R A T I O N

Tier selection 

and Profile 

development

C O M M U N I C A T I O N

Figure 6: Notional Collaboration and Communication Flows Within an Organization

Privacy posture, 

changes in risk, 

and 

implementation 

progress
NIST Privacy Framework Preliminary Draft September 6, 2019

14

472 Framework as a tool to support accountability. They can also use the Privacy Framework in conjunction 

473 with other frameworks and guidance that provide additional practices to achieve accountability within 

and between organizations (see section 3.5 on Use within the Data Processing Ecosystem).

9 474

475 Establishing or Improving a Privacy Program

476 Using a simple model of “ready, set, go” phases, the Privacy 

477 Framework can support the creation of a new privacy program or 

478 improvement of an existing program. These phases should be 

479 repeated as necessary to continuously improve privacy. 

480 Ready 

481 Effective privacy risk management requires an organization to 

482 understand its business or mission environment; its legal 

483 environment; its enterprise risk tolerance; the privacy risks 

484 engendered by its systems, products, or services; and its role or 

485 relationship to other organizations in the ecosystem. An 

486 organization can use the Identify-P and Govern-P Functions to “get 

487 ready” by reviewing the Categories and Subcategories, and 

beginning to develop its Current Profile and Target Profile.10 488 

489 An organization conducts privacy risk assessments pursuant to the 

490 Risk Assessment category of the Identify Function. It is important 

491 that an organization identifies emerging privacy risks to gain a 

492 better understanding of the impacts of its systems, products, or services on individuals. See Appendix D 

493 for more information on privacy risk assessments.

494 Set

495 The organization completes its Current Profile by indicating which Category and Subcategory outcomes 

496 from the remaining Functions are being achieved. If an outcome is partially achieved, noting this fact will 

497 help support subsequent steps by providing baseline information. Informed by its privacy risk 

498 assessment,the organization creates its Target Profile focused on the assessment of the Categories and 

499 Subcategories describing the organization’s desired privacy outcomes. An organization also may develop 

500 its own additional Functions, Categories, and Subcategories to account for unique organizational risks. It

501 may also consider influences and requirements of external stakeholders such as business customers and 

502 partners when creating a Target Profile. An organization can develop multiple Profiles to support its 

503 different business lines or processes, which may have different business needs and associated risk 

504 tolerances.

505 The organization compares the Current Profile and the Target Profile to determine gaps. Next, it creates 

506 a prioritized action plan to address gaps—reflecting mission drivers, costs and benefits, and risks—to 

507 achieve the outcomes in the Target Profile. An organization using the Cybersecurity Framework and the 

9 See, e.g., NIST Special Publication (SP) 800-37 Rev. 2, Risk Management Framework for Information Systems and 

Organizations: A System Life Cycle Approach for Security and Privacy at https://doi.org/10.6028/NIST.SP.800-37r2;

and Organization for the Advancement of Structured Information Standards (OASIS), Privacy Management 

Reference Model and Methodology (PMRM) Version 1.0 at https://docs.oasis-open.org/pmrm/PMRM/v1.0/PMRMv1.0.pdf.

10 For additional guidance, see the “Prepare” step, Section 3.1, NIST SP 800-37 Revision 2, Risk Management 

Framework for Information Systems and Organizations: A System Life Cycle Approach for Security and Privacy [6].

A Simplified Method for 

Establishing or Improving 

a Privacy Program

Ready: use the Identify-P 

and Govern-P Functions

to get “ready.”

Set: “set” an action plan 

based on the differences 

between Current and 

Target Profile(s).

Go: “go” forward with 

implementing the action 

plan.
NIST Privacy Framework Preliminary Draft September 6, 2019

15

508 Privacy Framework together may develop integrated action plans. The organization then determines 

509 resources, including funding and workforce, necessary to address the gaps, which can inform the 

510 selection of an appropriate Tier. Using Profiles in this manner encourages the organization to make 

511 informed decisions about privacy activities, supports risk management, and enables the organization to 

512 perform cost-effective, targeted improvements. 

513 Go

514 With the action plan “set,” the organization prioritizes which actions to take to address any gaps, and 

then adjusts its current privacy practices in order to achieve the Target Profile.11 515 For further guidance, 

516 informative references that support outcome achievement for the Categories and Subcategories are

517 available at https://www.nist.gov/privacy-framework. The organization should determine which 

518 standards, guidelines, and practices, including those that are sector specific, work best for its needs. 

519 An organization can cycle through the phases nonsequentially as needed to continuously assess and 

520 improve its privacy posture. For instance, an organization may find that more frequent repetition of the 

521 Ready phase improves the quality of risk assessments. Furthermore, an organization may monitor 

522 progress through iterative updates to the Current Profile or the Target Profile to adjust to changing risks, 

523 subsequently comparing the Current Profile to the Target Profile. An organization may also use this 

524 process to align its privacy program with its desired Tiers.

525 Applying to the System Development Life Cycle

526 The Privacy Framework can be applied throughout the system development life cycle (SDLC) phases of 

527 plan, design, build/buy, deploy, operate, and decommission. The plan phase of the SDLC begins the cycle 

528 of any system and lays the groundwork for everything that follows. Overarching privacy considerations 

529 should be declared and described as clearly as possible. The plan should recognize that those 

530 considerations and requirements are likely to evolve during the remainder of the life cycle. A key 

531 milestone of the design phase is validating that the system privacy requirements match the needs and 

532 risk tolerance of the organization as they were expressed in a Profile. The desired privacy outcomes 

533 prioritized in a Target Profile should be incorporated when a) developing the system during the build 

534 phase and b) purchasing or outsourcing the system during the buy phase. That same Target Profile 

535 serves as a list of system privacy features that should be assessed when deploying the system to verify 

536 that all features are implemented. The privacy outcomes determined by using the Privacy Framework 

537 should then serve as a basis for ongoing operation of the system. This includes occasional reassessment, 

538 capturing results in a Current Profile, to verify that privacy requirements are still fulfilled. 

539 Privacy risk assessments typically focus on the information life cycle, the stages through which 

540 information passes, often characterized as creation or collection, processing, dissemination, use, 

541 storage, and disposition, to include destruction and deletion. Aligning the SDLC and the information 

542 lifecycle by identifying and understanding how data are processed during all stages of the SDLC helps 

543 organizations to better manage privacy risks and informs the selection and implementation of privacy 

544 controls throughout the SDLC.

11 NIST SP 800-37 [6] provides additional guidance on steps to execute on the action plan, including control 

selection, implementation, and assessment to close any gaps.
NIST Privacy Framework Preliminary Draft September 6, 2019

16

545 Using within the Data Processing Ecosystem

546

547

548

549

550

551

552

553

554

555

556

557

558

559

560

561

562

563

564

565

566

The Privacy Framework provides 

a common language to 

communicate requirements with 

parties within the data 

processing ecosystem. As 

depicted in Figure 7, the data

processing ecosystem 

encompasses a range of entities 

and roles that may have 

complex, multi-directional 

relationships with each other 

and individuals. Complexity can 

increase when entities are 

supported by a chain of subentities; for example, service 

providers may be supported by 

a series of service providers, or 

manufacturers may have 

multiple component suppliers. 

In addition, Figure 7 displays 

entities as having distinct roles,

but organizations may have

multiple roles, such as an 

567

568

569

570

571

572

573

574

575

organization providing services to other organizations and providing retail products to consumers. The 

roles in Figure 7 are intended to be notional classifications. In practice, an organization’s role(s) may be 

legally codified—for example, some laws classify organizations as data controllers or data processors—

or classifications may be derived from industry sector designations. 

An organization should use the Privacy Framework from its standpoint in the data processing 

ecosystem and consider how to manage privacy risk not only with regard to its internal priorities, but 

also in relation to how they affect other parties’ management of privacy risk. An organization can use its 

576 Profiles to select Functions, Categories, and Subcategories that are relevant to its role(s). For example: 

577 • An organization may use a Target Profile to express privacy risk management requirements to

578 an external service provider (e.g., a cloud provider to which it is exporting data).

579 • An organization may express its privacy posture through a Current Profile to report results or to

580 compare with acquisition requirements.

581 • An industry sector may establish a Target Profile that can be used among its constituents as an

582 initial baseline Profile to build their own customized Target Profiles.

583 • An organization may use a Target Profile to determine the capabilities to build into its products

584 so that its business customers can meet the privacy needs of their end users.

585 Communication is especially important among entities in the data processing ecosystem. Organizational 

586 practices should address this management of privacy risk, including identifying, assessing, and mitigating

587 privacy risks arising from the processing of data, as well as from systems, products, and services that 

588 inherently lack the capabilities to mitigate privacy risks. Example activities may include: 

Figure 7: Data Processing Ecosystem Relationships
NIST Privacy Framework Preliminary Draft September 6, 2019

17

589 • Determining privacy requirements for service providers, 

590 • Enacting privacy requirements through formal agreement (e.g., contracts), 

591 • Communicating to service providers how those privacy requirements will be verified and 

592 validated, 

593 • Verifying that privacy requirements are met through a variety of assessment methodologies, 

594 and 

595 • Governing and managing the above activities.

596 Informing Buying Decisions

597 Since either a Current or Target Profile can be used to generate a prioritized list of organizational privacy 

598 requirements, these Profiles can also be used to inform decisions about buying products and services. By 

599 first selecting outcomes that are relevant to its privacy goals, the organization then can evaluate 

600 partners’ systems, products, or services against this outcome. For example, if a device is being 

601 purchased for environmental monitoring of a forest, manageability may be important to support 

602 capabilities for minimizing the processing of data about people using the forest and should drive a 

603 manufacturer evaluation against applicable Subcategories (e.g., CT.DP-P4 in Appendix A: system or 

604 device configurations permit selective collection or disclosure of data elements).

605 In circumstances where it may not be possible to impose a set of privacy requirements on the supplier, 

606 the objective should be to make the best buying decision among multiple suppliers, given a carefully 

607 determined list of privacy requirements. Often, this means some degree of trade-off, comparing 

608 multiple products or services with known gaps to the Profile. If the system, product, or service 

609 purchased did not meet all of the objectives described in the Profile, the organization could address the 

610 residual risk through mitigation measures or other management actions.
NIST Privacy Framework Preliminary Draft September 6, 2019

18

611 Appendix A: Privacy Framework Core

612 This appendix presents the Core: a table of Functions, Categories, and Subcategories that describe 

613 specific privacy activities that can support managing privacy risks when systems, products, and services 

614 are processing data. 

615 Note to Users

616 Under the Privacy Framework’s risk-based approach:

617 1. An organization may not need to achieve every outcome or activity reflected in the Core. It is

618 expected that an organization will use Profiles to select and prioritize the Functions, Categories,

619 and Subcategories that best meet its specific needs by considering its organizational or industry

620 sector goals, legal/regulatory requirements and industry best practices, the organization’s risk

621 management priorities, and the privacy needs of individuals who are directly or indirectly served

622 or affected by the organization’s systems, products, or services. The Subcategories should not

623 be read as a checklist in isolation from their Categories, which often provide a risk-based

624 modifier on Subcategory selection.

625 2. It is not obligatory to achieve an outcome in its entirety. An organization may use its Profiles to

626 express partial achievement of an outcome, as not all aspects of an outcome may be relevant

627 for the organization to manage privacy risk, or the organization may use a Target Profile to

628 express an aspect of an outcome that it does not currently have the capability to achieve.

629 3. It may be necessary to consider multiple outcomes in combination to appropriately manage

630 privacy risk. For example, an organization that responds to individuals’ requests for data access

631 may select for its Profile both the Subcategory CT.DM-P1: “Data elements can be accessed for

632 review” and the Category “Identity Management, Authentication, and Access Control” (PR.AC-P)

633 to ensure that only the individual to whom the data pertain gets access.

634 Implementation: The table format of the Core is not intended to suggest a specific implementation 

635 order or imply a degree of importance between the Functions, Categories, and Subcategories. 

636 Implementation may be nonsequential, simultaneous, or iterative, depending on the SDLC stage, status 

637 of the privacy program, or scale of the workforce. In addition, the Core is not exhaustive; it is extensible, 

638 allowing organizations, sectors, and other entities to adapt or add additional Functions, Categories, and

639 Subcategories to their Profiles.

640 Roles: 

641 • Workforce: Different parts of an organization’s workforce may take responsibility for different

642 Categories or Subcategories. For example, the legal department may be responsible for carrying

643 out activities under “Governance Policies, Processes, and Procedures” while the IT department

644 is working on “Inventory and Mapping.” Ideally, the Core encourages cross-organization

645 collaboration to develop Profiles and achieve outcomes.

646 • Ecosystem: The Core is intended to be usable by any organization or entity regardless of its role

647 in the data processing ecosystem. Although the Privacy Framework does not classify ecosystem

648 roles, an organization should review the Core from its standpoint in the ecosystem. An

649 organization’s role(s) may be legally codified—for example, some laws classify organizations as

650 data controllers or data processors—or classifications may be derived from industry

651 designations. Since Core elements are not assigned by ecosystem role, an organization can use

652 its Profiles to select Functions, Categories, and Subcategories that are relevant to its role(s).
NIST Privacy Framework Preliminary Draft September 6, 2019

19

653 Scalability: Certain aspects of outcomes may be ambiguously worded. For example, outcomes may 

654 include terms like “communicated” or “disclosed” without stating to whom the communications or 

655 disclosures are being made. The ambiguity is intentional to allow for a wide range of organizations with 

656 different use cases to determine what is appropriate or required in a given context.

657 Resource Repository: Additional supporting resources, including informative references that can 

658 provide more guidance on how to achieve an outcome can be found on the NIST website at

659 https://www.nist.gov/privacy-framework.

660 Cybersecurity Framework Alignment: 

661 • Figure 8 uses the Venn diagram from section 1.2.1 to demonstrate that the Privacy Framework

662 Functions: Identify-P, Govern-P, Control-P, and Communicate-P can be used to manage privacy

663 risks arising from data processing. Protect-P, Detect, Respond, and Recover can help

664 organizations manage privacy risks associated with privacy breaches. Because Detect, Respond,

665 and Recover are cybersecurity incident-related, these Functions are greyed out in Table 1

666 because they are not part of the Privacy Framework, although organizations can find them in

667 the Cybersecurity Framework and use them to further support the management of the privacy

668 breach aspect of privacy risk. Alternatively, organizations may use the Cybersecurity Framework

669 Functions in conjunction with Identify-P, Govern-P, Control-P, and Communicate-P to

670 collectively address privacy and cybersecurity risks.

671 • Certain Categories or Subcategories may be identical to or have been adapted from the

672 Cybersecurity Framework. The following legend can be used to identify this relationship in Table

673 2.

674

675

676

677

678 Core Identifiers: For ease of use, each component of the Core is given a unique identifier. Functions and 

679 Categories each have a unique alphabetic identifier, as shown in Table 1. Subcategories within each 

680 Category have a number added to the alphabetic identifier; the unique identifier for each Subcategory is 

681 included in Table 2. 

The Category or Subcategory is identical to the Cybersecurity Framework.

The Function, Category, or Subcategory aligns with the Cybersecurity 

Framework, but the text has been adapted for the Privacy Framework.

Cybersecurity 

Risks 

Privacy 

Risks

Privacy 

Breach Risks

IDENTIFY-P

GOVERN-P

CONTROL-P

COMMUNICATE-P

PROTECT-P

RECOVER

DETECT

RESPOND

IDENTIFY

PROTECT

RECOVER

DETECT

RESPOND

Figure 8: Using Functions to Manage Privacy Risk
NIST Privacy Framework Preliminary Draft September 6, 2019

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682 Table 1: Privacy Framework Function and Category Unique Identifiers

683 Function 

Unique 

Identifier

Function Category 

Unique 

Identifier

Category

ID-P Identify-P ID.IM-P Inventory and Mapping

ID.BE-P Business Environment

ID.RA-P Risk Assessment

ID.DE-P Data Processing Ecosystem Risk Management

GV-P Govern-P GV.PP-P Governance Policies, Processes, and Procedures

GV.RM-P Risk Management Strategy

GV.AT-P Awareness and Training

GV.MT-P Monitoring and Review

CT-P Control-P CT.PO-P Data Management Policies, Processes, and Procedures

CT.DM-P Data Management

CT.DP-P Disassociated Processing

CM-P Communicate-P CM.PP-P Communication Policies, Processes, and Procedures

CM.AW-P Data Processing Awareness

PR-P Protect-P PR.AC-P Identity Management, Authentication, and Access 

Control

PR.DS-P Data Security

PR.DP-P Data Protection Policies, Processes, and Procedures

PR.MA-P Maintenance

PR.PT-P Protective Technology

DE Detect DE.AE Anomalies and Events

DE.CM Security Continuous Monitoring

DE.DP Detection Processes

RS Respond RS.RP Response Planning

RS.CO Communications

RS.AN Analysis

RS.MI Mitigation

RS.IM Improvements

RC Recover RC.RP Recovery Planning

RC.IM Improvements

RC.CO Communications
NIST Privacy Framework Preliminary Draft September 6, 2019

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684 Table 2: Privacy Framework Core

Function Category Subcategory

IDENTIFY-P (IDP): Develop the 

organizational 

understanding 

to manage 

privacy risk for 

individuals 

arising from 

data 

processing.

Inventory and Mapping (ID.IM-P): Data 

processing by systems, products, or services 

is understood and informs the management 

of privacy risk.

ID.IM-P1: Systems/products/services that process data are inventoried.

ID.IM-P2: Owners or operators (e.g., the organization or third parties 

such as service providers, partners, customers, and developers) and 

their roles with respect to the systems/products/services and 

components (e.g., internal or external) that process data are 

inventoried.

ID.IM-P3: Categories of individuals (e.g., customers, employees or 

prospective employees, consumers) whose data are being processed 

are inventoried.

ID.IM-P4: Data actions of the systems/products/services are 

inventoried.

ID.IM-P5: The purposes for the data actions are inventoried.

ID.IM-P6: Data elements within the data actions are inventoried.

ID.IM-P7: The data processing environment is identified (e.g., 

geographic location, internal, cloud, third parties).

ID.IM-P8: Data processing is mapped, illustrating the data actions and 

associated data elements for systems/products/services, including 

components; roles of the component owners/operators; and 

interactions of individuals or third parties with the 

systems/products/services.

Business Environment (ID.BE-P): The 

organization’s mission, objectives, 

stakeholders, and activities are 

understood and prioritized; this 

information is used to inform privacy roles, 

responsibilities, and risk management

decisions.

ID.BE-P1: The organization’s role in the data processing ecosystem

is identified and communicated.

ID.BE-P2: Priorities for organizational mission, objectives, and 

activities are established and communicated.

ID.BE-P3: Systems/products/services that support organizational 

priorities are identified and key requirements communicated.
NIST Privacy Framework Preliminary Draft September 6, 2019

22

Function Category Subcategory

Risk Assessment (ID.RA-P): The 

organization understands the privacy risks

to individuals and how such privacy risks 

may create follow-on impacts on 

organizational operations, including 

mission, functions, other risk management

priorities (e.g., compliance, financial), 

reputation, workforce, and culture.

ID.RA-P1: Contextual factors related to the systems/products/services 

and the data actions are identified (e.g., individuals’ demographics and 

privacy interests or perceptions, data sensitivity, visibility of data 

processing to individuals and third parties). 

ID.RA-P2: Data analytic inputs and outputs are identified and evaluated 

for bias.

ID.RA-P3: Potential problematic data actions and associated problems 

are identified. 

ID.RA-P4: Problematic data actions, likelihoods, and impacts are 

used to determine and prioritize risk.

ID.RA-P5: Risk responses are identified, prioritized, and 

implemented.

Data Processing Ecosystem Risk 

Management (ID.DE-P): The organization’s 

priorities, constraints, risk tolerances, and 

assumptions are established and used to 

support risk decisions associated with 

managing privacy risk and third parties 

within the data processing ecosystem. The 

organization has established and 

implemented the processes to identify, 

assess, and manage privacy risks within 

the data processing ecosystem.

ID.DE-P1: Data processing ecosystem risk management processes 

are identified, established, assessed, managed, and agreed to by 

organizational stakeholders.

ID.DE-P2: Data processing ecosystem parties (e.g., service providers, 

customers, partners, product manufacturers, application 

developers) are identified, prioritized, and assessed using a privacy 

risk assessment process.

ID.DE-P3: Contracts with data processing ecosystem parties are 

used to implement appropriate measures designed to meet the 

objectives of an organization’s privacy program. 

ID.DE-P4: Interoperability frameworks or similar multi-party 

approaches are used to manage data processing ecosystem privacy 

risks. 

ID.DE-P5: Data processing ecosystem parties are routinely assessed 

using audits, test results, or other forms of evaluations to confirm 

they are meeting their contractual or framework obligations.

GOVERN-P (GV-P):

Develop and 

implement the 

Governance Policies, Processes, and 

Procedures (GV.PP-P): The policies, 

processes, and procedures to manage and 

GV.PP-P1: Organizational privacy values and policies (e.g., 

conditions on data processing, individuals’ prerogatives with respect 

to data processing) are established and communicated.
NIST Privacy Framework Preliminary Draft September 6, 2019

23

Function Category Subcategory

organizational 

governance 

structure to 

enable an ongoing 

understanding of 

the organization’s 

risk management 

priorities that 

are informed by 

privacy risk.

monitor the organization’s regulatory, 

legal, risk, environmental, and operational 

requirements are understood and inform 

the management of privacy risk.

GV.PP-P2: Processes to instill organizational privacy values within 

system/product/service development and operations are established 

and in place.

GV.PP-P3: Roles and responsibilities for the workforce are 

established with respect to privacy. 

GV.PP-P4: Privacy roles and responsibilities are coordinated and 

aligned with third-party stakeholders (e.g., service providers, 

customers, partners).

GV.PP-P5: Legal, regulatory, and contractual requirements regarding 

privacy are understood and managed.

GV.PP-P6: Governance and risk management policies, processes,

and procedures address privacy risks.

Risk Management Strategy (GV.RM-P): 

The organization’s priorities, constraints, 

risk tolerances, and assumptions are 

established and used to support 

operational risk decisions.

GV.RM-P1: Risk management processes are established, managed, 

and agreed to by organizational stakeholders.

GV.RM-P2: Organizational risk tolerance is determined and clearly 

expressed.

GV.RM-P3: The organization’s determination of risk tolerance is 

informed by its role in the data processing ecosystem.

Awareness and Training (GV.AT-P): The 

organization’s workforce and third parties 

engaged in data processing are provided 

privacy awareness education and are 

trained to perform their privacy-related 

duties and responsibilities consistent with 

related policies, processes, procedures, 

and agreements and organizational privacy 

values.

GV.AT-P1: The workforce is informed and trained on its roles and 

responsibilities.

GV.AT-P2: Senior executives understand their roles and 

responsibilities.

GV.AT-P3: Privacy personnel understand their roles and 

responsibilities.

GV.AT-P4: Third parties (e.g., service providers, customers, partners) 

understand their roles and responsibilities.

Monitoring and Review (GV.MT-P): The 

policies, processes, and procedures for 

ongoing review of the organization’s privacy 

GV.MT-P1: Privacy risk is re-evaluated on an ongoing basis and as key 

factors, including the organization’s business environment, governance 

(e.g., legal obligations, risk tolerance), data processing, and 

systems/products/services change.
NIST Privacy Framework Preliminary Draft September 6, 2019

24

Function Category Subcategory

posture are understood and inform the 

management of privacy risk.

GV.MT-P2: Privacy values, policies, and training are reviewed and any 

updates are communicated. 

GV.MT-P3: Policies, processes, and procedures for assessing

compliance with legal requirements and privacy policies are established 

and in place.

GV.MT-P4: Policies, processes, and procedures for communicating 

progress on managing privacy risks are established and in place.

GV.MT-P5: Policies, processes, and procedures are established and in 

place to receive, analyze, and respond to problematic data actions

disclosed to the organization from internal and external sources (e.g., 

internal discovery, privacy researchers).

GV.MT-P6: Policies, processes, and procedures incorporate lessons 

learned from problematic data actions.

GV.MT-P7: Policies, processes, and procedures for receiving, tracking, 

and responding to complaints, concerns, and questions from 

individuals about organizational privacy practices are established and in 

place.

CONTROL-P (CTP): Develop and 

implement 

appropriate 

activities to enable 

organizations or 

individuals to 

manage data with 

sufficient 

granularity to 

manage privacy 

risks.

Data Management Policies, Processes, and 

Procedures (CT.PO-P): Policies, processes, 

and procedures are maintained and used to 

manage data processing (e.g., purpose, 

scope, roles, responsibilities, management 

commitment, and coordination among 

organizational entities) consistent with the 

organization’s risk strategy to protect 

individuals’ privacy.

CT.PO-P1: Policies, processes, and procedures for authorizing data 

processing (e.g., organizational decisions, individual consent), revoking 

authorizations, and maintaining authorizations are established and in 

place.

CT.PO-P2: Policies, processes, and procedures for enabling data review, 

transfer, sharing or disclosure, alteration, and deletion are established 

and in place.

CT.PO-P3: Policies, processes, and procedures for enabling individuals’ 

data processing preferences and requests are established and in place.

CT.PO-P4: An information life cycle to manage data is aligned and 

implemented with the system development life cycle to manage 

systems.

Data Management (CT.DM-P): Data are 

managed consistent with the organization’s 

risk strategy to protect individuals’ privacy, 

CT.DM-P1: Data elements can be accessed for review.

CT.DM-P2: Data elements can be accessed for transmission or 

disclosure.
NIST Privacy Framework Preliminary Draft September 6, 2019

25

Function Category Subcategory

increase manageability, and enable the 

implementation of privacy principles (e.g., 

individual participation, data quality, data 

minimization). 

CT.DM-P3: Data elements can be accessed for alteration.

CT.DM-P4: Data elements can be accessed for deletion.

CT.DM-P5: Data are destroyed according to policy.

CT.DM-P6: Data are transmitted using standardized formats.

CT.DM-P7: Metadata containing processing permissions and related 

data values are transmitted with data elements.

CT.DM-P8: Audit/log records are determined, documented, 

implemented, and reviewed in accordance with policy and 

incorporating the principle of data minimization.

Disassociated Processing (CT.DP-P): Data 

processing solutions increase disassociability

consistent with related policies, processes, 

procedures, and agreements and the 

organization’s risk strategy to protect 

individuals’ privacy.

CT.DP-P1: Data are processed in an unobservable or unlinkable manner 

(e.g., data actions take place on local devices, privacy-preserving 

cryptography).

CT.DP-P2: Data are processed to limit the identification of individuals 

(e.g., differential privacy techniques, tokenization).

CT.DP-P3: Data are processed to restrict the formulation of inferences 

about individuals’ behavior or activities (e.g., data processing is 

decentralized, distributed architectures).

CT.DP-P4: System or device configurations permit selective collection 

or disclosure of data elements.

CT.DP-P5: Attribute references are substituted for attribute values.

CT.DP-P6: Data processing is limited to that which is relevant and 

necessary for a system/product/service to meet mission/business 

objectives.

COMMUNICATE-P 

(CM-P): Develop 

and implement 

appropriate 

activities to enable 

organizations and 

individuals to have 

a reliable 

understanding 

Communication Policies, Processes, and 

Procedures (CM.PP-P): Policies, processes, 

and procedures are maintained and used to 

increase transparency of the organization’s 

data processing practices (e.g., purpose, 

scope, roles, responsibilities, management 

commitment, and coordination among 

organizational entities) and associated 

privacy risks.

CM.PP-P1: Transparency policies, processes, and procedures for

communicating data processing purposes, practices, and associated

privacy risks are established and in place.

CM.PP-P2: Roles and responsibilities (e.g., public relations) for

communicating data processing purposes, practices, and associated

privacy risks are established.
NIST Privacy Framework Preliminary Draft September 6, 2019

26

Function Category Subcategory

about how data 

are processed and 

associated privacy 

risks.

Data Processing Awareness (CM.AW-P):

Individuals and organizations have reliable 

knowledge about data processing practices 

and associated privacy risks, and effective 

mechanisms are used and maintained to 

increase predictability consistent with the 

organization’s risk strategy to protect 

individuals’ privacy. 

CM.AW-P1: Mechanisms (e.g., notices, internal or public reports) for

communicating data processing purposes, practices, associated privacy

risks, and options for enabling individuals’ data processing preferences

and requests are established and in place.

CM.AW-P2: Mechanisms for obtaining feedback from individuals (e.g.,

surveys or focus groups) about data processing and associated privacy

risks are established and in place.

CM.AW-P3: System/product/service design enables data processing

visibility.

CM.AW-P4: Records of data disclosures and sharing are maintained

and can be accessed for review or transmission/disclosure.

CM.AW-P5: Data corrections or deletions can be communicated to

individuals or organizations (e.g., data sources) in the data processing

ecosystem.

CM.AW-P6: Data provenance and lineage are maintained and can be

accessed for review or transmission/disclosure.

CM.AW-P7: Impacted individuals and organizations are notified about

a privacy breach or event.

CM.AW-P8: Individuals are provided with mitigation mechanisms to

address impacts to individuals that arise from data processing.

PROTECT-P 

(PR-P): Develop 

and implement 

appropriate 

data processing 

safeguards.

Identity Management, Authentication, 

and Access Control (PR.AC-P): Access to 

data and devices is limited to authorized 

individuals, processes, and devices, and is 

managed consistent with the assessed risk

of unauthorized access.

PR.AC-P1: Identities and credentials are issued, managed, verified, 

revoked, and audited for authorized individuals, processes, and 

devices.

PR.AC-P2: Physical access to data and devices is managed.

PR.AC-P3: Remote access is managed.

PR.AC-P4: Access permissions and authorizations are managed, 

incorporating the principles of least privilege and separation of 

duties.

PR.AC-P5: Network integrity is protected (e.g., network segregation, 

network segmentation).
NIST Privacy Framework Preliminary Draft September 6, 2019

27

Function Category Subcategory

PR.AC-P6: Individuals and devices are proofed and bound to 

credentials, and authenticated commensurate with the risk of the 

transaction (e.g., individuals’ security and privacy risks and other 

organizational risks).

Data Security (PR.DS-P): Data are 

managed consistent with the 

organization’s risk strategy to protect 

individuals’ privacy and maintain data 

confidentiality, integrity, and availability.

PR.DS-P1: Data-at-rest are protected.

PR.DS-P2: Data-in-transit are protected.

PR.DS-P3: Systems/products/services and associated data are 

formally managed throughout removal, transfers, and disposition.

PR.DS-P4: Adequate capacity to ensure availability is maintained.

PR.DS-P5: Protections against data leaks are implemented.

PR.DS-P6: Integrity checking mechanisms are used to verify 

software, firmware, and information integrity.

PR.DS-P7: The development and testing environment(s) are 

separate from the production environment.

PR.DS-P8: Integrity checking mechanisms are used to verify 

hardware integrity.

Data Protection Policies, Processes, and 

Procedures (PR.DP-P): Security and 

privacy policies (which address purpose,

scope, roles, responsibilities, management 

commitment, and coordination among 

organizational entities), processes, and 

procedures are maintained and used to 

manage the protection of data.

PR.DP-P1: A baseline configuration of information technology is 

created and maintained incorporating security principles (e.g.,

concept of least functionality).

PR.DP-P2: Configuration change control processes are established 

and in place.

PR.DP-P3: Backups of information are conducted, maintained, and 

tested.

PR.DP-P4: Policy and regulations regarding the physical operating 

environment for organizational assets are met.

PR.DP-P5: Protection processes are improved.

PR.DP-P6: Effectiveness of protection technologies is shared.

PR.DP-P7: Response plans (Incident Response and Business 

Continuity) and recovery plans (Incident Recovery and Disaster 

Recovery) are established, in place, and managed.

PR.DP-P8: Response and recovery plans are tested.
NIST Privacy Framework Preliminary Draft September 6, 2019

28

Function Category Subcategory

PR.DP-P9: Privacy procedures are included in human resources 

practices (e.g., deprovisioning, personnel screening).

PR.DP-P10: A vulnerability management plan is developed and 

implemented.

Maintenance (PR.MA-P): System 

maintenance and repairs are performed 

consistent with policies, processes, and 

procedures.

PR.MA-P1: Maintenance and repair of organizational assets are 

performed and logged, with approved and controlled tools.

PR.MA-P2: Remote maintenance of organizational assets is 

approved, logged, and performed in a manner that prevents 

unauthorized access.

Protective Technology (PR.PT-P):

Technical security solutions are managed 

to ensure the security and resilience of 

systems/products/services and associated 

data, consistent with related policies, 

processes, procedures, and agreements.

PR.PT-P1: Removable media is protected and its use restricted 

according to policy.

PR.PT-P2: The principle of least functionality is incorporated by 

configuring systems to provide only essential capabilities.

PR.PT-P3: Communications and control networks are protected.

PR.PT-P4: Mechanisms (e.g., failsafe, load balancing, hot swap) are 

implemented to achieve resilience requirements in normal and 

adverse situations.

685
NIST Privacy Framework Preliminary Draft September 6, 2019

29

686 Appendix B: Glossary

687 This appendix defines selected terms used for the purposes of this publication.

Attribute Reference

(NIST SP 800-63-3 [7]) 

A statement asserting a property of a subscriber without necessarily 

containing identity information, independent of format. For example, for 

the attribute “birthday,” a reference could be “older than 18” or “born in 

December.”

Attribute Value

(NIST SP 800-63-3 [7])

A complete statement asserting a property of a subscriber, independent 

of format. For example, for the attribute “birthday,” a value could be 

“12/1/1980” or “December 1, 1980.”

Availability 

[NIST SP 800-37 [6])

Ensuring timely and reliable access to and use of information.

Category The subdivision of a Function into groups of privacy outcomes closely tied 

to programmatic needs and particular activities.

Communicate-P

(Function)

Develop and implement appropriate activities to enable organizations 

and individuals to have a reliable understanding about how data are 

processed and associated privacy risks.

Confidentiality

[NIST SP 800-37 [6])

Preserving authorized restrictions on information access and disclosure, 

including means for protecting personal privacy and proprietary 

information.

Control-P (Function) Develop and implement appropriate activities to enable organizations or 

individuals to manage data with sufficient granularity to manage privacy 

risks.

Core A set of privacy protection activities and outcomes. The Framework Core 

comprises three elements: Functions, Categories, and Subcategories.

Cybersecurity Incident

(OMB 17-12 [8])

An occurrence that (1) actually or imminently jeopardizes, without lawful 

authority, the integrity, confidentiality, or availability of information or an 

information system; or (2) constitutes a violation or imminent threat of 

violation of law, security policies, security procedures, or acceptable use 

policies.

Data A representation of information, including digital and non-digital formats.

Data Action

(Adapted from NIST IR 

8062 [5])

A system/product/service data life cycle operation, including, but not 

limited to collection, retention, logging, generation, transformation, use, 

disclosure, sharing, transmission, and disposal.

Data Element The smallest named item of data that conveys meaningful information.

Data Processing

(Adapted from NIST IR 

8062 [5])

The collective set of data actions (i.e., the complete data life cycle, 

including, but not limited to collection, retention, logging, generation, 

transformation, use, disclosure, sharing, transmission, and disposal).

Data Processing 

Ecosystem

The complex and interconnected relationships among entities involved in 

creating or deploying systems, products, or services or any components 

that process data.

Disassociability

(Adapted from NIST IR 

8062 [5])

Enabling the processing of data or events without association to 

individuals or devices beyond the operational requirements of the 

system.

Function A component of the Core that provides the highest level of structure for 

organizing basic privacy activities into Categories and Subcategories.
NIST Privacy Framework Preliminary Draft September 6, 2019

30

Govern-P (Function) Develop and implement the organizational governance structure to 

enable an ongoing understanding of the organization’s risk management 

priorities that are informed by privacy risk.

Identify-P (Function) Develop the organizational understanding to manage privacy risk for 

individuals arising from data processing.

Implementation Tier Provides a point of reference on how an organization views privacy risk 

and whether it has sufficient processes and resources in place to manage 

that risk.

Individual A single person or a group of persons, including at a societal level.

Integrity

[NIST SP 800-37 [6])

Guarding against improper information modification or destruction, and 

includes ensuring information non-repudiation and authenticity.

Lineage The history of processing of a data element, which may include point-topoint data flows and the data actions performed upon the data element. 

Manageability

(Adapted from NIST IR 

8062 [5])

Providing the capability for granular administration of data, including 

alteration, deletion, and selective disclosure.

Metadata

(Adapted from NIST SP 

800-53 [9])

Information describing the characteristics of data including, for example, 

structural metadata describing data structures (i.e., data format, syntax, 

semantics) and descriptive metadata describing data contents.

Predictability

(Adapted from NIST IR 

8062 [5])

Enabling reliable assumptions by individuals, owners, and operators 

about data and its processing by a system, product, or service.

Privacy Breach

(Adapted from OMB M17-12 [8])

The loss of control, compromise, unauthorized disclosure, unauthorized 

acquisition, or any similar occurrence where (1) a person other than an 

authorized user accesses or potentially accesses data or (2) an authorized 

user accesses data for an other than authorized purpose. 

Privacy Control

[Adapted from NIST SP 

800-37 [6])

The administrative, technical, and physical safeguards employed within 

an organization to satisfy privacy requirements.

Privacy Requirement A specification for system/product/service functionality to meet 

stakeholders’ desired privacy outcomes.

Privacy Risk The likelihood that individuals will experience problems resulting from 

data processing, and the impact should they occur.

Privacy Risk Assessment A privacy risk management sub-process for identifying, evaluating, 

prioritizing, and responding to specific privacy risks.

Privacy Risk 

Management

A cross-organizational set of processes for identifying, assessing, and 

responding to privacy risks.

Problematic Data Action

(Adapted from NIST IR 

8062 [5])

A data action that could cause an adverse effect for individuals.

Processing See Data Processing.

Profile A selection of specific Functions, Categories, and Subcategories from the 

Core that the organization has prioritized to help it manage privacy risk.

Protect-P (Function) Develop and implement appropriate data processing safeguards.

Provenance

(Adapted from NIST IR 

8112 [10])

Metadata pertaining to the origination or source of specified data.
NIST Privacy Framework Preliminary Draft September 6, 2019

31

Risk

(NIST SP 800-30 [11])

A measure of the extent to which an entity is threatened by a potential 

circumstance or event, and typically a function of: (i) the adverse impacts 

that would arise if the circumstance or event occurs; and (ii) the 

likelihood of occurrence.

Risk Management The process of identifying, assessing, and responding to risk.

Subcategory The further divisions of a Category into specific outcomes of technical 

and/or management activities.

688
NIST Privacy Framework Preliminary Draft September 6, 2019

32

689 Appendix C: Acronyms

690 This appendix defines selected acronyms used in the publication.

691

692 IEC International Electrotechnical Commission

693 IR Internal Report

694 ISO International Organization for Standardization

695 IT Information Technology

696 NIST National Institute of Standards and Technology

697 OASIS Organization for the Advancement of Structured Information Standards

698 OECD Organisation for Economic Co-operation and Development

699 OMB Office of Management and Budget

700 PMRM Privacy Management Reference Model and Methodology

701 PRAM Privacy Risk Assessment Methodology

702 SDLC System Development Life Cycle

703 SP Special Publication
NIST Privacy Framework Preliminary Draft September 6, 2019

33

704 Appendix D: Privacy Risk Management Practices 

705 Section 1.2 introduces a number of considerations around privacy risk management, including the 

706 relationship between cybersecurity and privacy risk and the role of privacy risk assessment. This 

707 appendix considers some of the key practices that contribute to successful privacy risk management, 

708 including organizing preparatory resources, determining privacy capabilities, defining privacy 

709 requirements, conducting privacy risk assessments, creating privacy requirements traceability, and 

710 monitoring for changing privacy risks. Category and Subcategory references are included to facilitate use 

711 of the Core to support these practices; these references appear in parentheticals. 

712 Organizing Preparatory Resources

713 The right resources facilitate informed decision-making about privacy risks at all levels of an 

714 organization. As a practical matter, the responsibility for the development of various resources may 

715 belong to different components of the organization. Therefore, a component of the organization 

716 depending on certain resources may find that they either do not exist, or may not sufficiently address 

717 privacy. In these circumstances, the dependent component can consider the purpose of the resource 

718 and either seek the information through other sources or make the best decision it can with the 

719 available information. In short, good resources are helpful, but any deficiencies should not prevent

720 organizational components from making the best risk decisions they can within their capabilities. 

721 The following resources, while not exhaustive, build a foundation for better decision-making.

722 • Risk management role assignments (GV.PP-P3, GV.PP-P4)

723 Enabling cross-organizational understanding of who has responsibility for different risk

724 management tasks in the organization supports better coordination and accountability for

725 decision-making. In addition, a broad range of perspectives can improve the process of

726 identifying, assessing, and responding to privacy risks. A diverse and cross-functional team can

727 help to identify a more comprehensive range of risks to individuals’ privacy, and to select a

728 wider set of mitigations. Determining which roles to include in the risk management discussions

729 depends on organizational context and makeup, although collaboration between an

730 organization’s privacy and cybersecurity programs will be important. If one individual is being

731 assigned to multiple roles, managing potential conflicts of interest should be considered.

732 • Enterprise risk management strategy (GV.RM-P)

733 An organization’s enterprise risk management strategy helps to align the organization’s mission

734 and values with organizational risk assumptions and constraints. Limitations on resources to

735 achieve mission/business objectives and to manage a broad portfolio of risks will likely require

736 trade-offs. Enabling personnel involved in the privacy risk management process to better

737 understand the organization’s risk tolerance should help to guide decisions about how to

738 allocate resources and improve decisions around risk response.

739 • Key stakeholders (GV.PP-P4, ID.DE-P)

740 Privacy stakeholders are those who have an interest or concern in the privacy outcomes of the

741 system, product, or service. For example, legal concerns likely focus on whether the system,

742 product, or service is operating in a way that would cause the organization to be out of

743 compliance with privacy laws or regulations or its business agreements. Business owners that

744 want to maximize usage may be concerned about loss of trust in the system, product, or service

745 due to poor privacy. Individuals whose data are being processed or who are interacting with the
NIST Privacy Framework Preliminary Draft September 6, 2019

34

746 system, product, or service will be interested in not experiencing problems or adverse 

747 consequences. Understanding the stakeholders and the types of privacy outcomes they are 

748 interested in will facilitate system/product/service design that appropriately addresses 

749 stakeholders’ needs.

750 • Organizational-level privacy requirements (GV.PP-P)

751 Organizational-level privacy requirements are a means of expressing the legal obligations,

752 privacy values, and policies to which the organization intends to adhere. Understanding these

753 requirements is key to ensuring that the system/product/service design complies with its

754 obligations. Organizational-level privacy requirements may be derived from a variety of sources,

755 including:

756 o Legal environment (e.g., laws, regulations, contracts),

757 o Organizational policies or cultural values,

758 o Relevant standards, and

759 o Privacy principles.

760 • System/product/service design artifacts (ID.BE-P3)

761 Design artifacts may take many forms such as system design architectures or data flow

762 diagrams. These artifacts help an organization build systems, products, and services that meet

763 an organization’s mission/business priorities and objectives. Therefore, they can help privacy

764 programs understand how systems, products, and services need to function so that controls or

765 measures that help to mitigate privacy risk can be selected and implemented in ways that

766 maintain functionality while protecting privacy.

767 • Data maps (ID.IM-P)

768 Data maps illustrate data processing and individuals’ interactions with systems, products, and

769 services. A comprehensive data map shows the data processing environment and includes the

770 components through which data are being processed or with which individuals are interacting,

771 the owners or operators of the components, and discrete data actions and the specific data

772 elements being processed. A data map can be overlaid on existing system/product/service

773 design artifacts for convenience and ease of communication between organizational

774 components. As discussed below, a data map is an important artifact in privacy risk assessment.

775 Determining Privacy Capabilities

776 Privacy capabilities can be used to describe the system, product, or service property or feature that 

777 achieves the desired privacy outcome (e.g., “the service enables data minimization.”) Security system 

778 engineers use the security objectives confidentiality, integrity, and availability along with organizational779 level security requirements to consider the security capabilities for a system, product, or service. As set 

780 forth in Table 3, NIST has developed an additional set of privacy engineering objectives to support the 

781 determination of privacy capabilities. An organization may also use the privacy engineering objectives as 

782 a high-level prioritization tool. Systems, products, or services that are low in predictability, 

783 manageability, or disassociability may be a signal of increased privacy risk, and therefore merit a more 

784 comprehensive privacy risk assessment. 

785 In determining privacy capabilities, an organization may consider which of the privacy engineering and 

786 security objectives are most important with respect to its mission/business needs, risk tolerance, and 
NIST Privacy Framework Preliminary Draft September 6, 2019

35

787 organizational-level privacy requirements (see Organizing Preparatory Resources above). Not all of the 

788 objectives may be equally important, or trade-offs may be necessary among them. Although the privacy 

789 capabilities inform the privacy risk assessment by supporting risk prioritization decisions, the privacy 

790 capabilities may also be informed by the risk assessment and adjusted to support the management of 

791 specific privacy risks or address changes in the environment, including design changes to the system, 

792 product, or service.

Table 3: Privacy Engineering and Security Objectives12 793

Objective Definition

Principal Related 

Functions from the 

Privacy Framework Core

Privacy Engineering 

Objectives

Predictability Enabling reliable assumptions by individuals, 

owners, and operators about data and its 

processing by a system

Identify-P, Govern-P, 

Control-P, CommunicateP, Protect-P

Manageability Providing the capability for granular 

administration of data, including alteration, 

deletion, and selective disclosure

Identify-P, Govern-P, 

Control-P

Disassociability Enabling the processing of data or events 

without association to individuals or devices 

beyond the operational requirements of the 

system

Identify-P, Govern-P, 

Control-P

Security Objectives

Confidentiality Preserving authorized restrictions on 

information access and disclosure, including 

means for protecting personal privacy and 

proprietary information

Identify-P, Govern-P, 

Protect-P

Integrity Guarding against improper information 

modification or destruction; includes ensuring 

information non-repudiation and authenticity

Identify-P, Govern-P, 

Protect-P

Availability Ensuring timely and reliable access to and use 

of information

Identify-P, Govern-P, 

Protect-P

794 Defining Privacy Requirements

795 Privacy requirements specify the way the system, product, or service needs to function to meet 

796 stakeholders’ desired privacy outcomes (e.g., “the application is configured to allow users to select 

797 specific data elements”). To define privacy requirements, consider organizational-level privacy 

798 requirements (see Organizing Preparatory Resources above) and the outputs of a privacy risk 

799 assessment. This process helps an organization to answer two questions: 1) what a system, product, or 

800 service can do with data processing and interactions with individuals, and 2) what it should do. Then an 

801 organization can allocate resources to design a system, product, or service in a way that achieves the 

802 defined requirements. Ultimately, this can lead to the development of systems, products, and services 

803 that are more mindful of individuals’ privacy, and are based on informed risk decisions.

12 The privacy engineering objectives are adapted from NIST IR 8062, An Introduction to Privacy Engineering and 

Risk Management in Federal Systems [5]. The security objectives are from NIST SP 800-37 Revision 2, Risk 

Management Framework for Information Systems and Organizations: A System Life Cycle Approach for Security 

and Privacy [6].
NIST Privacy Framework Preliminary Draft September 6, 2019

36

804 Conducting Privacy Risk Assessments

805 Conducting a privacy risk assessment helps an organization to identify privacy risks engendered by the 

806 system, product, or service and prioritize them to be able to make informed decisions about how to 

807 respond to the risks (ID.RA-P, GV.RM-P). Methodologies for conducting privacy risk assessments may 

vary, but organizations should consider the following characteristics:13 808

809 • Risk model (ID.RA-P, GV.MT-P1)

Risk models define the risk factors to be assessed and the relationships among those factors.14 810 If

811 an organization is not using a pre-defined risk model, the organization should clearly define

812 which risk factors it will be assessing and the relationships among these factors. Although

813 cybersecurity has a widely used risk model

814 based on the risk factors of threats,

815 vulnerabilities, likelihood, and impact,

816 there is not one commonly accepted

817 privacy risk model. NIST has developed a

818 privacy risk model based on the risk factors of problematic data actions, likelihood, and impact,

819 each explained below.

820 o A problematic data action is any action a system takes to process data that could result in a

821 problem for individuals. Organizations consider the type of problems that are relevant to

822 the population of individuals. Problems can take any form and may consider the experience

of individuals singly or as a group.15 823

824 o Likelihood is defined as a contextual analysis that a data action is likely to create a problem

825 for a representative set of individuals. Context can include organizational factors (e.g., the

826 public perception about participating organizations with respect to privacy), system factors

827 (e.g., the nature and history of individuals’ interactions with the system, visibility of data

828 processing to individuals and third parties), or individual factors (e.g., individuals’

demographics, privacy interests or perceptions, data sensitivity).16 829 A data map can help with

830 this contextual analysis (see Organizing Preparatory Resources).

831 o Impact is an analysis of the costs should the problem occur. As noted in section 1.2, the

832 experience of individuals is a type of externality for organizations. Moreover, individuals’

833 experiences may be subjective. Thus, impact may be difficult to assess accurately.

834 Organizations should consider the best means of internalizing impact to individuals in order

to appropriately prioritize and respond to privacy risks.17 835

13 NIST has developed a Privacy Risk Assessment Methodology (PRAM) that can help organizations identify, assess, 

and respond to privacy risks. It is comprised of a set of worksheets available at [3].

14 See NIST SP 800-30 Rev. 1, Guide for Conducting Risk Assessments at [11] p. 8.

15 As part of its PRAM, NIST has created an illustrative catalog of problematic data actions and problems for 

consideration [3]. Other organizations may have created additional problem sets, or may refer to them as adverse 

consequences or harms.

16 See NIST PRAM for more information about contextual factors. Id at Worksheet 2.

17 The NIST PRAM uses organizational costs such as non-compliance costs, direct business costs, reputational costs, 

and internal culture costs as drivers for considering how to assess individual impact. Id at Worksheet 3, Impact Tab.

NIST Privacy Risk Factors:

Problematic Data Action | Likelihood | Impact
NIST Privacy Framework Preliminary Draft September 6, 2019

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836 • Assessment approach

837 The assessment approach is the mechanism by which identified risks are prioritized. Assessment 

approaches can be categorized as quantitative, semi-quantitative, or qualitative.

18 19 838

839 • Prioritizing risks (ID.RA-P4)

840 Given the applicable limits of an organization’s resources, organizations prioritize the risks to 

facilitate communication about how to respond.

20 841

842 • Responding to risks (ID.RA-P5)

843 As described in section 1.2.2, responding to risk is usually categorized as mitigation, 

transfer/sharing, avoidance, or acceptance.21 844

845 Creating Privacy Requirements Traceability

846 Once the organization has determined which risks to mitigate, the organization can refine the privacy 

847 requirements and then select and implement controls (i.e., technical and/or policy safeguards) to meet 

the defined requirements.22 848 An organization may use a variety of sources to select controls, such as NIST 

SP 800-53, Security and Privacy Controls for Information Systems and Organizations.23 849 After 

850 implementation, an organization iteratively assesses the controls for their effectiveness in meeting the 

851 privacy requirements and managing privacy risk. In this way, an organization creates traceability 

852 between the controls and the privacy requirements, and demonstrates accountability between its 

853 systems, products, and services and its organizational privacy goals.

854 Monitoring Changing Privacy Risks

855 Privacy risk management is not a static process. An organization monitors how changes in its business 

856 environment and corresponding changes to its systems, products, and services may be affecting privacy 

857 risk, and iteratively use the practices in this appendix to adjust accordingly. (GV.MT-P1)

 

18 See NIST SP 800-30 Rev. 1, Guide for Conducting Risk Assessments at [11] p. 14.

19 The NIST PRAM uses a semi-quantitative approach based on a scale of 1-10.

20 The NIST PRAM provides various prioritization representations, including a heat map. See [3] Worksheet 3.

21 The NIST PRAM provides a process for responding to prioritized privacy risks. Id at Worksheet 4.

22 See NIST SP 800-37 Rev. 2, Risk Management Framework for Information Systems and Organizations: A System 

Life Cycle Approach for Security and Privacy at [6].

23 See NIST SP 800-53, Security and Privacy Controls for Information Systems and Organizations, as updated at [9]. 
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858 Appendix E: Implementation Tiers Definitions

859 The Tiers are defined through four areas summarized below: 

860 Tier 1: Partial

861 • Privacy Risk Management Process – Organizational privacy risk management practices are not

862 formalized, and risk is managed in an ad hoc and sometimes reactive manner. Prioritization of

863 privacy activities may not be directly informed by organizational risk objectives, privacy risk

864 assessments, or business/mission requirements.

865 • Integrated Privacy Risk Management Program – There is limited awareness of privacy risk at

866 the organizational level. The organization implements privacy risk management on an irregular,

867 case-by-case basis due to varied experience or information gained from outside sources. The

868 organization may not have processes that enable the sharing of information about data

869 processing and resulting privacy risks within the organization.

870 • Data Processing Ecosystem Relationships – There is limited understanding of an organization’s

871 role in the larger ecosystem with respect to other entities (e.g., buyers, suppliers, service

872 providers, business associates, partners). The organization does not have processes for

873 identifying how privacy risks may proliferate throughout the ecosystem or for communicating

874 privacy risks or requirements to other entities in the ecosystem.

875 • Workforce – Some personnel may have a limited understanding of privacy risks or privacy risk

876 management processes, but have no specific privacy responsibilities. If available, privacy

877 training is ad hoc and the content is not kept current with best practices.

878 Tier 2: Risk Informed

879 • Privacy Risk Management Process – Risk management practices are approved by management

880 but may not be established as organization-wide policy. Prioritization of privacy activities is

881 directly informed by organizational risk objectives, privacy risk assessments, and

882 business/mission requirements.

883 • Integrated Privacy Risk Management Program – There is an awareness of privacy risk at the

884 organizational level, but an organization-wide approach to managing privacy risk has not been

885 established. Information about data processing and resulting privacy risks is shared within the

886 organization on an informal basis. Consideration of privacy in organizational objectives and

887 programs may occur at some but not all levels of the organization. Privacy risk assessment

888 occurs, but is not typically repeatable or reoccurring.

889 • Data Processing Ecosystem Relationships – There is some understanding of an organization’s

890 role in the larger ecosystem with respect to other entities (e.g., buyers, suppliers, service

891 providers, business associates, partners). The organization is aware of the privacy ecosystem

892 risks associated with the products and services it provides and uses, but does not act

893 consistently or formally upon those risks.

894 • Workforce – There are personnel with specific privacy responsibilities, but they may have non895 privacy responsibilities as well. Privacy training is conducted regularly for privacy personnel,

896 although there is no consistent process for updates on best practices.
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897 Tier 3: Repeatable

898 • Privacy Risk Management Process – The organization’s risk management practices are formally

899 approved and expressed as policy. Organizational privacy practices are regularly updated based

900 on the application of risk management processes to changes in business/mission requirements

901 and a changing risk, policy, and technology landscape.

902 • Integrated Privacy Risk Management Program – There is an organization-wide approach to

903 manage privacy risk. Risk-informed policies, processes, and procedures are defined,

904 implemented as intended, and reviewed. Consistent methods are in place to respond effectively

905 to changes in risk. The organization consistently and accurately monitors privacy risk. Senior

906 privacy and non-privacy executives communicate regularly regarding privacy risk. Senior

907 executives ensure consideration of privacy through all lines of operation in the organization.

908 • Data Processing Ecosystem Relationships – The organization understands its role,

909 dependencies, and dependents in the larger ecosystem and may contribute to the community’s

910 broader understanding of risks. The organization is aware of the privacy ecosystem risks

911 associated with the products and services it provides and it uses. Additionally, it usually acts

912 formally upon those risks, including mechanisms such as written agreements to communicate

913 baseline requirements, governance structures, and policy implementation and monitoring.

914 • Workforce – Dedicated privacy personnel possess the knowledge and skills to perform their

915 appointed roles and responsibilities. There is regular, up-to-date privacy training for all

916 personnel.

917 Tier 4: Adaptive

918 • Privacy Risk Management Process – The organization adapts its privacy practices based on

919 lessons learned from privacy breaches and events, and identification of new privacy risks.

920 Through a process of continuous improvement incorporating advanced privacy technologies and

921 practices, the organization actively adapts to a changing policy and technology landscape and

922 responds in a timely and effective manner to evolving privacy risks.

923 • Integrated Privacy Risk Management Program – There is an organization-wide approach to

924 managing privacy risk that uses risk-informed policies, processes, and procedures to address

925 problematic data actions. The relationship between privacy risk and organizational objectives is

926 clearly understood and considered when making decisions. Senior executives monitor privacy

927 risk in the same context as cybersecurity risk, financial risk, and other organizational risks. The

928 organizational budget is based on an understanding of the current and predicted risk

929 environment and risk tolerance. Business units implement executive vision and analyze system930 level risks in the context of the organizational risk tolerances. Privacy risk management is part of

931 the organizational culture and evolves from lessons learned and continuous awareness of data

932 processing and resulting privacy risks. The organization can quickly and efficiently account for

933 changes to business/mission objectives in how risk is approached and communicated.

934 • Data Processing Ecosystem Relationships – The organization understands its role,

935 dependencies, and dependents in the larger ecosystem and contributes to the community’s

936 broader understanding of risks. The organization uses real-time or near-real-time information to

937 understand and consistently act upon privacy ecosystem risks associated with the products and

938 services it provides and it uses. Additionally, it communicates proactively, using formal (e.g.,

939 agreements) and informal mechanisms to develop and maintain strong ecosystem relationships.
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940 • Workforce – The organization has specialized privacy skillsets throughout the organizational 

941 structure; personnel with diverse perspectives contribute to the management of privacy risks. 

942 There is regular, up-to-date, specialized privacy training for all personnel. Personnel at all levels 

943 understand the organizational privacy values and their role in maintaining them.

944
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945 Appendix F: Roadmap

946 This appendix will provide a companion roadmap to the Privacy Framework covering next steps and 

947 identifying key areas where the relevant practices are not well enough understood to enable 

948 organizations to achieve a privacy outcome. These areas will be based on input and feedback received 

949 from stakeholders through the Privacy Framework development process.
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950 Appendix G: References

[1] National Institute of Standards and Technology (2018) Framework for Improving Critical

Infrastructure Cybersecurity, Version 1.1. (National Institute of Standards and Technology,

Gaithersburg, MD). https://doi.org/10.6028/NIST.CSWP.04162018

[2] National Institute of Standards and Technology (2019) Summary Analysis of the Responses to the

NIST Privacy Framework Request for Information. (National Institute of Standards and

Technology, Gaithersburg, MD).

https://www.nist.gov/sites/default/files/documents/2019/02/27/

rfi_response_analysis_privacyframework_2.27.19.pdf

[3] National Institute of Standards and Technology (2019) NIST Privacy Risk Assessment

Methodology (PRAM). (National Institute of Standards and Technology, Gaithersburg, MD).

https://www.nist.gov/itl/applied-cybersecurity/privacy-engineering/resources

[4] The Smart Grid Interoperability Panel—Smart Grid Cybersecurity Committee (2014) Guidelines

for Smart Grid Cybersecurity: Volume 1 - Smart Grid Cybersecurity Strategy, Architecture, and

High-Level Requirements. (National Institute of Standards and Technology, Gaithersburg, MD).

NIST Internal Report (IR) 7628, Rev. 1, Vol. 1. https://doi.org/10.6028/NIST.IR.7628r1

[5] Brooks S., Garcia M., Lefkovitz N., Lightman S., Nadeau E. (2017) An Introduction to Privacy

Engineering and Risk Management in Federal Systems. (National Institute of Standards and

Technology, Gaithersburg, MD). NIST Internal Report (IR) 8062.

https://doi.org/10.6028/NIST.IR.8062

[6] Joint Task Force (2018) Risk Management Framework for Information Systems and Organizations:

A System Life Cycle Approach for Security and Privacy. (National Institute of Standards and

Technology, Gaithersburg, MD). NIST Special Publication (SP) 800-37 Rev. 2.

https://doi.org/10.6028/NIST.SP.800-37r2

[7] Grassi P., Garcia M., Fenton J. (2017) Digital Identity Guidelines. (National Institute of Standards

and Technology, Gaithersburg, MD). NIST Special Publication (SP) 800-63-3.

https://csrc.nist.gov/publications/detail/sp/800-63/3/final

[8] Office of Management and Budget (OMB), Preparing for and Responding to a Breach of

Personally Identifiable Information, OMB Memorandum 17-12, January 3, 2017. Available at

https://www.whitehouse.gov/sites/whitehouse.gov/files/omb/memoranda/2017/m-17-

12_0.pdf

[9] Joint Task Force (2017) Security and Privacy Controls for Information Systems and Organizations.

(National Institute of Standards and Technology, Gaithersburg, MD). NIST Special Publication (SP)

800-53, multiple revisions. https://csrc.nist.gov/publications/sp800-53

[10] Grassi P., Lefkovitz N., Nadeau E., Galluzzo R., Dinh A. (2018) Attribute Metadata: A Proposed

Schema for Evaluating Federated Attributes. (National Institute of Standards and Technology,

Gaithersburg, MD). NIST Internal Report (IR) 8112. https://doi.org/10.6028/NIST.IR.8112

[11] Joint Task Force Transformation Initiative (2012) Guide for Conducting Risk Assessments.

(National Institute of Standards and Technology, Gaithersburg, MD). NIST Special Publication (SP)

800-30 Rev. 1. https://doi.org/10.6028/NIST.SP.800-30r1

951