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Towards an Internet of Trusted Data:

A New Framework for Identity and Data Sharing

August 2016

Input to the Commission on Enhancing National Cybersecurity

Alex Pentland David Shrier Thomas Hardjono Irving Wladawsky-Berger

pentland@mit.edu shrier@mit.edu hardjono@mit.edu irvingwb@mit.edu

Massachusetts Institute of Technology

connection.mit.edu
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Towards an Internet of Trusted Data:

A New Framework for Identity and Data Sharing

Summary of recommendations from a July 2016 meeting at MIT with senior executives from

AT&T, IBM, MasterCard, Qualcomm and U.S. Departments of Treasury and Commerce, as

reported by MIT Connection Science leadership.

I. Executive Summary

As the economy and society move from a world where interactions were physical and based on

paper documents, toward a world that is primarily governed by digital data and digital

transactions, our existing methods of managing identity and data security are proving

inadequate. Large-scale fraud, identity theft and data breaches are becoming common, and a

large fraction of the population have only the most limited digital credentials. Even so, our

Digital Infrastructure is recognized as a Strategic National Asset which must be resilient to

threat. If we can create an Internet of Trusted Data that provides safe, secure access for

everyone, then huge societal benefits can be unlocked, including better health, greater financial

inclusion, and a population that is more engaged with and better supported by its government.

The future of National Cyber Security should be supported by an Internet of Trusted Data in

order to enable both auditable provenance of identity and the credibility of data. in order to

enhance economic viability of new technology solutions, policies and best practices. 

Simultaneously, an Internet of Trusted Data must protect the privacy of people, ensure public

safety, economic and national security, and foster public, individual and business partnerships.

In order to accomplish these goals thought leaders in federal, state and local governments

should join with academia and carrier-scale private industry to work toward an Internet of

Trusted Data.

An Internet of Trusted Data includes:

• Robust Digital Identity. Identity, whether personal or organizational, is the key that

unlocks all other data and data sharing functions. Digital Identity includes not only

having unique and unforgeable credentials that work everywhere, but also the ability to

access all the data linked to your identity and the ability to control the “persona” that

you present in different situations. These pseudonym identities, or personas, include

the “work you”, the “health system you”, the “government you” and many other

permutations specific to particular aspects of your individual relationship with another

party. Each of these pseudonym identities will have different data access associated

with them, and be owned and controlled only by the core “biological you”. To

accomplish this there needs to be a global strategy for Identity and Access Management

that genuinely enables trusted, auditable sharing relationships and functions without

compromising personal anonymity or security. This is technically straightforward: the
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basics were established by the NIST’s National Strategy for Trusted Identity in

Cyberspace program and now are widely available from, for instance, mobile operators

and similar regulated services. The nation now needs to begin requiring such robust

digital identity in order to achieve our goals in cybersecurity and universal access.

• Distributed Internet Trust Authorities. We have repeatedly seen that centralized

system administration is the weakest link in cybersecurity, enabling both insiders and

opponents to destroy our system security with a single exploit. The most practical

solution to this problem is to have authority distributed among many trusted actors, so

that compromise of one or even a few authorities does not destroy the system security

consensus. This already standard practice for the highest security systems: no one

single actor can launch nuclear missiles, for instance. Now we need to implement this

sort of consensus security widely. Examples such as the blockchain that underlies most

digital cryptocurrencies show that distributed ledgers can provide world-wide security

even in very hostile environments. Today there is a huge amount of investment by

private companies to deploy software defined network technology which can

transparently expose efficient, convenient versions of this consensus ledger technology,

and the U.S. should set policies that take advantage of these new capabilities in

collaboration with the private and education sectors, in such a way that digital identities

can be originated by individuals and issued with verification from multiple access

providers.

• Distributed safe computation. Our critical systems will suffer increasing rates of

damage and compromise unless we move decisively toward pervasive use of data

minimization, more encryption and distributed computation. Current firewall, event

sharing, and attack detection approaches are simply not feasible as long-run solutions

for cybersecurity, and we need to adopt an inherently more robust approach. The

“optimal” technology for such an inherently safe data ecosystem is currently being built

and tested, for reference see MIT’s Enigma project. Because of the importance of acting

quickly, the EU data protection authorities are supporting a simplified, easy-to-deploy

version called OPAL (Open Algorithms, which originated at MIT with French support) for

pilot testing within certain countries. The concept of OPAL is that instead of copying or

sharing data, algorithms are sent to existing databases, executed behind existing

firewalls, and only the encrypted results are shared. This minimizes opportunities to

attack databases or divert data for unapproved use, but places restrictions on the ability

of an ecosystem to collaborate on data when it is in an encrypted state. Note that OPAL

may be combined with anonymization identifying elements in order to reduce risk, and

in the long run will evolve toward a fully-encrypted, computation friendly model.

Approaches such as homomorphic encryption and secure multiparty computation can

enable encrypted data to be used in approved, auditable manner by parties that can’t

decrypt it or read it. In particular, the ability to permissibly ask questions of data in the

form of “attributes” will be a key pattern to maintaining digital privacy while enabling

innovation ecosystems. The U.S. Government should create a roadmap for progressing
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from the current situation, through transition technologies such as OPAL, to complete

solutions such as MIT Enigma. 

• Universal Access. The advantages of secure digital infrastructure are diminished

without universal access. The U.S. Government can promote universal access by policies

that provide for secure, citizen-controlled Personal Data Stores for all citizens in a

manner analogous to current physical Post Office Boxes, and promote their use by

making government benefits and interactions such as tax transfers and information

inquiries conveniently available by mobile devices and web interfaces secured by the

citizens’ digital identity. Planning by the U.S. Post Office for such universal Personal

Data Stores (Digital Mailboxes) has long been in place, and the secure digital identity

infrastructure is already offered by mobile operators and other regulated services.

Investment required. 

We recommend that the U.S. Government establish a “Living Lab” to not just test, but actually

create a small-scale deployment of this new ecosystem under real-world conditions with all

available and necessary technology in order to obtain citizen and stakeholder feedback. A

Living Lab would prove concept and build citizen confidence towards large scale deployment

and prove viability of technical solutions. We also recommend that the U.S. Government

support “microdegrees” leveraging distance education methods (e.g., MOOC, etc.) in order to

upgrade the cybersecurity training of the existing workforce. Such continuing education

methods have proven quite cost-effective in changing the technology culture within U.S.

companies.

The Living Lab provides a venue where researchers and developers can begin to address

challenges around the Internet of Trusted Data, providing them with real-world conditions

under which a robust identity system must be deployable with distributed trust authorities, as

exemplified by proposals to use blockchain technology. It also permits data sharing to be

explored at scale while preserving privacy, where algorithms are sent to existing data

repositories based on distributed safe computation. Key to the Living Lab is universal access to

the benefits of the convergence of these new solutions.
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II. Introduction

Our economies and societies are going through a historical transition from the industrial age of

the past two centuries, - whose models have been mostly based on physical interactions, - to an

increasingly digital age based on global, digital interactions. Previous methods for managing

identity and data security have proved inadequate in our emerging digital world, and have led

to serious cybersecurity breaches.

A number of failure modes emerge at the current transition point. 

 While economy and society are becoming digital, identity remains rooted in analog

concepts. The consequences of issues such as identity theft include massive fraud,

ranging from bank and insurance to tax and even Uber and AirBnb. A parallel issue

emerges of equity and fairness: robust digital identities must be available to all

individuals.

 Commercial and government organizations have traditionally built silos of IT systems

and data stores each are largely incompatible with each other. In order to move to the

next level of a digital economy and to attain the speed and efficiency of business moving

at the speed of the network, there must be interoperability and sharing to foster public,

private and individual collaboration on trusted data. It must be efficient and based on

universally agreed protocols while maintaining security and auditability.

At the same time, our increasingly digital world is opening up opportunities for economic

inclusion, improved health care, better financial support and populations that are more

engaged with and supported by their government.

To help address these threats and opportunities, President Obama issued an Executive Order

earlier this year establishing the Commission on Enhancing National Cybersecurity within the

Department of Commerce. The Commission was charged with “recommending bold, actionable

steps that the government, private sector, and the nation as a whole can take to bolster

cybersecurity in today’s digital world, and reporting back by the beginning of December.”

The Commission invited select members of this working group to participate in a panel on

research and development opportunities at a public meeting held in New York City on May 16.

In our testimony to the Commission we highlighted six key areas where government,

technology companies and academia should work together in order to Increase the speed and

quality of the two-way information flows that are essential for developing a data-rich society

with a holistic approach to cyber protection:

 Proof of Identity. A new identity management system must be created to replace

today's ad hoc systems.
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 Trustworthy, auditable data provenance. Systems must automatically track every

change that is made to data, so it is auditable and completely trustworthy.

 Secure, privacy-preserving processing. We have to enable the entities to engage in

transactions and to verify that contracts are being fulfilled but without revealing private

or confidential information.

 Universal access. Everyone must be able to share in the benefits, and have the

protections, of this new trusted data infrastructure

 Research and development. We need to dramatically increase the speed and scale of

cyber innovation in both the private and public sector by use of “living lab” field trials

 Workforce development. Companies face a serious shortage of cyber trained personnel

and of management expertise in cybersecurity. We need to increase and maintain the

available workforce, which may require greater educational capacity and incentives.

We also emphasized that the essential importance of focusing on complete systems, rather

than individual technologies or technology layers, and that they be developed and proven in

"living laboratories" with a representative population of users in order to provide feedback

about the relevance, efficiency, effectiveness, and ethical dimensions of these new systems.

In discussions with the U.S. Secretary of Commerce, the White House panel on cybersecurity,

and the E.U. VP of Single Digital Market, we were encouraged to create a plan for

accomplishing these goals that brought together key players from government, industry, and

academia.

On July 11 we convened a workshop at MIT to start framing our statement of the problem as

well as our recommendations. The workshop participants all agreed that we are at a unique

point to move forward, much as was the case with the Internet and World Wide Web in the

early 1990. As was the case then, there is a growing consensus on: 

1. The problems to be solved:

• The need to bolster cybersecurity in our increasingly digital economy and society

• A requirement for universal, highly secure digital identities covering individuals,

private and public institutions and "things" (IoT).

• The need to efficiently access, exchange and share critical data with full security

and privacy protection.

• The overall systems have to be "fault tolerant" in the presence of "non-trusted"

actors, whether they are competitors or other governments you only want to

share limited data with, or "bad actors" with malicious intent.
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2. The fact that there is promising evolution of a new set of general technologies and

potential solutions to help address these problems, including:

 Identity, whether personal or organizational, and, moreover, the ability to own

and assert identity attributes is a lynchpin concern. There needs to be a kind of

"internet of identity" to genuinely enable all other sharing functions.

 Blockchain networks can provide a single source of auditable truth between

organizations and some level of appropriate automation of data processing. 

However, organizations must decide also on distributed sources of trust for the

moderation) of such networks. Identity plays a crucial role in enabling blockchain

technology to be adopted broadly.

 Overlaying inventions such as personal data stores and secure multiparty

computation (see for reference implementations MIT OpenPDS and MIT Enigma),

we can develop a new digital ecosystem that is secure, trusted, and empowering.

3. The need for the private sector, government and academia to work together to

address these critical problems and leverage these promising technologies to enable

and incentivize collaboration and innovation.

At the same time, the population needs to be educated in a coherent fashion about the

benefits and role that each individual can play in forming this new system.

While the question arises “are we simply replacing known risks with unknown risks?”, the

shortcomings of existing systems are proving so great that a new approach is needed

In light of these concerns, we have articulated potential solutions around Robust Identity and

Trusted Data which enable the auditability and credibility of both while supporting Fair

Information Practice Principles.
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III. The Promise of Robust Identity:

Our mission in suggesting a robust identity framework focuses on connecting the individual

with the digital identity, while protecting privacy. When we say “robust”, we mean both

reliable and non-forgeable.

Benefits include better access:

 to the financial system for the underbanked and unbanked;

 to the health care system, in a fashion that reduces medical error and improves care;

 to government services;

 to other basic services (e.g., making it easier to obtain an apartment or home).

Drivers of need

A number of problems are driving the need for a robust identity:

 It is fundamental to cybersecurity. Current cybersecurity systems are insufficient to the

task, as evidenced by the numerous large-scale data breaches recently experienced by

both the private and public sectors globally.

 We all need identity to access services.

 The flaws in translating from a physical proof of identity (“I see you in front of me, I

know you are you”), to a digital format (“On the internet, no one knows you are a dog”),

in a robust and portable fashion.

 The question of authority: who provides the identity?

 The need for it to be unique, strong, verifiable, and non-forgeable.

A potential solution

A new paradigm asserts that you are your digital footprint, and you have ownership rights in

your data. Just as the Magna Carta established a framework for individual property rights in

1215 A.D., so too a new digital social contract needs to provide for digital ownership rights.

The concept of behavioral biometrics is gaining ground in areas such as financial services and

digital authentication. Research conducted at MIT and elsewhere has demonstrated that

behavior biometrics are much more difficult to fabricate and deliver 10X+ better security than

password-based models1

. With respect to ownership rights: this “New Deal on Data” was first

posed by us in collaboration with the World Economic Forum in 2009 and expanded since2

.

Several challenges need to be addressed, including, but not limited to:

 “Big Brother”: the fear of a government using panoptic access for dictatorship;

 Bad actors: whether inside an organization or external, accumulating such data creates

risk of misuse by bad actors;

 Scale and implementation cost: implementing such a solution globally will have

nontrivial scaling and cost functions (and relatedly, who will pay for it and how?);
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 Undocumented residents: deploying such a system creates potential for

institutionalizing a digital divide between rich and poor, and introduces new questions

around circumstances such as where municipalities offer undocumented residents a

means of identification even if the Federal government hasn’t;

 Equal protection under the law: how can we protect someone that the system doesn’t

acknowledge has an existence?

 Universal vs. silo’d data: universal data has greater utility, but is generally less secure –

siloing can provide a measure of security, but raises issues of interoperability; and

 Regulatory lag: there is always a gap between a technology innovation and the ability of

policymakers and regulators to implement an appropriate framework around it.

Questions also remain as to how this would be developed. Should it be government led, like

the EID or India or Estonia? Should it be furnished by industry, similar to how Internet Domain

Name registries are handled? Should it be housed within a nonprofit or academic environment,

like the Kerberos Consortium or the World Wide Web Consortium (W34C)? Active dialog with

key stakeholders is required to establish the optimal path.

Potential Solution: Core Identities and Persona Identities

At the heart of digital identities is the concept of the core identity of an individual, which

inalienably belongs to that individual. The core identity serves as the quantum from which

emerge other forms of digitally-derived identities (called personas), that are practically useful

and are legally enforced in digital transactions. An individual must have the freedom to choose

to deploy one or more digital personas on the Internet, each used with specific sharing and

access permission and tailored to the specific aspect of that individual’s life. Each digital

personal would carry varying degrees of legal enforceability as relevant to the auditable usage

context of that persona.

The individual must be able to use transaction-identities derived from his or her relevant

persona, without affecting the privacy of their core identity. This derivation process must also

allow the relying party (counterparty) in a transaction to validate the source-authenticity and

strength of provenance of the transaction identity, without affecting the privacy of the core

identity of the user. New cryptographic techniques – such as zero knowledge proofs – offer a

promising direction in providing solutions for privacy-preserving core identities.

As currently configured, existing business models, legal instruments and technical

implementations are insufficient to support this type of identity ecosystem. This is because

something is missing: an architecture for individual ownership of and primacy over one’s own

core identity and which entities or relationships have access to attributes of that identity. With

such a core identity, it is possible for multiple aliases, accounts and attributes to be

authenticated and authorized in a reliable, privacy enhancing and scalable manner. To this end,

a viable identity infrastructure provides a way for each person to own their single underlying
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core identity and to bind several ”personas” to that core identity without the need for other

parties to access the core identity or be aware of any other personas. With this approach,

government issued identity credentials such as driver licenses, passports, professional licenses,

birth certificates, etc.) as well as strong-provenanced sources of attributes about a person (e.g.

banks for credit scores, etc) can be leveraged to create a core identity that remains private to

the end-user.

A key feature of the new model is that it must allow entities in the ecosystem to (i) verify the

“quality” or security of an identity, and (ii) to assess the relative “freedom” or independence of

an identity from any given authority (e.g. government, businesses, etc.), and (iii) to assess the

source of trust for a digital identity.

We believe a new model for digital identities for future blockchain systems is required, which is

summarized in the following progressive steps:

1. Strong provenanced attributes: It must be founded on an existing real-world identity

which has a high degree of source of trust, where its attributes have a high degree of

provenance. This identity maybe issued by an existing identity provider or other trusted

third party operating within a legal jurisdiction (e.g. Bank, Government, Service

Provider, etc.).

2. Transitive source of trust: Create a “Core Identity” based on the existing high quality

identity. That is, use a privacy-preserving algorithm that translates the existing realworld identity with strong provenance into a digital core-identity which carries-over the

source of trust.

3. Self-issued derived identities as personas: Provide users with the freedom (and

algorithms/tools) to establish personas and to self-issue anonymous but verifiable

transaction-identities, each of which is cryptographically derived from the user’s coreidentity and each of which carries specific permissioned attributes suitable for the

purpose of the transaction-identities. The source of trust from the core-identity must

also be carried-over into the derived transaction-identity.

4. Privacy-preserving verification: Provide the Relying Parties (counter-party) with a

privacy-preserving verification algorithms to validate the source of trust for any given

(anonymous) transaction-identity. These verification algorithms must allow a relying

party to establish a chain of provenance (from the transaction-identity all the way back

to the origin attributes and core-identity), while preserving the privacy of the owner of

the identity.

5. Legal Trust Framework (LTF): Establish an identity ecosystem for blockchain based on a

LTF for core-identities, personas and anonymous transaction-identities. Such a legal
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framework is already in use for identity-federation schemes in the industry today, and

may be used as the legal basis for this new model.

A legal trust framework is a certification program that enables a party who accepts a digital

identity credential (called the relying party) to trust the identity, security, and privacy policies of

the party who issues the credential (called the identity service provider) and vice versa. An LTF

applies within a given deployment ecosystem, such as identity-federation or across two partner

organizations.

We believe the current LTFs as practiced in the industry can be extended for usage in

blockchain systems. New types of entities will be needed specifically for blockchain ecosystems. 

We denote these as the Core-Identity Provider and Transaction-Identity Providers which

extends the current role of the Identity Provider (IdP).

The Core-Identity Provider takes a user's existing identity which has a high degree of source of

trust and converts it using a privacy-preserving function into a private or secret core identity

that is maintained as private or secret, and is only supplied to the Transaction-Identity Provider.

The later then provides a transaction-identity issuance service to the user, as well as a

validation service to the relying parties. The user is free to obtain one or more anonymous

transaction-identities from the Transaction-Identity Provider or self-issue a derived transactionidentity, all the while maintaining their privacy. The transaction-identities can be used on the

blockchain system with other users (relying parties) or on the Internet. The validation service

offered by the Transaction-Identity Provider allows a relying-party to inquire about the status

and source-grade of a given anonymous transaction-identity prior to transacting.

In the context of blockchains, the LTF provides the following:

• Network scalability: It allows any two parties to transact on a blockchain without prior

engagement, thus achieving network scalability.

• Provenance assessment: It allows a relying-party (counter-party) to assess the

“trustworthiness” (provenance and quality) of an (anonymous) transaction-identity prior

to commencing the transaction;

• Cross-jurisdiction interoperability: It provides a legal foundation for core-identities and

(anonymous) transaction-identities to be recognized in differing legal jurisdictions;

• New business models: It incentivizes service-providers (including the Core-Identity

Providers and Transaction-identity Providers) to develop new business models around

new scalable services and permissible use of attribute data associated with identities;

• Risk assessment and risk management: It provides entities in the ecosystem with a

means of assessing risk and of legal recourse in unforeseen circumstances (e.g. attacks

to the service; identity leaks; identity-data theft, provider negligence, etc.) as specified

in the LTF operational contracts.
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IV. Data Sharing

Data is rapidly proliferating from an end-user perspective, without a good solution to manage

user data as well as identities efficiently. We need a new paradigm for data sharing that

preserves user privacy, while allowing data to be shared more globally for the benefit of

society.

The constituents served by this new system include both enterprises and average consumers. 

By bringing control back to the consumer, both data and identity we can drive better outcomes. 

We can create technology that would enable the simplification and securing the digital

identities through simpler “form factors.”

Questions remain – what exactly does this solution look like? Could it be like Global Entry? Who

would manage such a system? In Global Entry’s case, it’s the TSA.

With respect to R&D, there’s a great diversity of work required, and we need to an approach

such as outlined in Section V. Opportunities created from this solution include the creation of

digital marketplace for personal data, that would simultaneously provide assurance of your

data.

Key Concepts in a Potential Solution

Data sharing in a privacy preserving manner requires a new view on data. There are a number

of key concepts and design principles that need to be addressed through an evolutionary proofof-concept (PoC) implementation. Some of these key concepts are as follows:

(1) Moving the algorithm to the data: The concept here is to perform the algorithm

(i.e. query) execution at the location of data (referred to as the data-repository). This

implies that raw-data should never leave its repository, and access to it is controlled by

the repository/data owner.

(2) Open Algorithms: Algorithms (i.e. queries or scripts) must be openly published,

studied and vetted by experts to be “safe” from violating the privacy requirements and

other requirements stemming from the context of their use.

(3) Permissible Use: When performing computation on attributes or data

associated with identities, respect the explicit and implicit permission, or consent, given

for use of the data or identity attributes as part of the transaction.

(4) Always return “safe answers” (never raw data): When performing computation

(e.g. in answering a query), the data-repository must always return “safe answers” and

never raw data. This concept seeks to address the issue of data privacy and the potential

danger of de-identification (of Personally Identifying Information, or PII) through the

correlation of multiple responses.
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(5) Data always in encrypted state: Data should be encrypted at all times, namely

at-rest, in-transit and during computation. Data should not need to be decrypted prior

to computation and then re-encrypted afterwards. Advanced cryptographic techniques

are now emerging that allows limited forms of computations to be performed on the

encrypted data. There two broad scenarios we seek to address:

• Computation by individual repository: Here, computation over encrypted data

is performed by a single repository, which may employ a physically distributed

set of nodes (e.g. P2P collaboration network) to collaboratively store parts of the

data for increased resiliency against attacks. Cryptographic techniques such as

secret-sharing provides for interesting possibilities in addressing these

requirements.

• Collaborative computation by multiple parties (multiparty computation): Some

form of queries may require answers to be computed by multiple participants

(e.g. repositories) in a collaborative/quorum method whilst maintain the privacy

of data stored at each repository. Each participant may see the final groupcomputed value, but they must not see each other’s raw data. Cryptographic

techniques such as Multi-Party Computation (MPC) offer a path forward in

solving these scenarios.

(6) Networked Collaboration Environments and Blockchains for audit and

accountability: Peer-to-Peer (P2P) networks – such as those underlying the Hyperledger

system – offers an attractive solution for data resiliency and scalability specially when

combined with cryptographic techniques such as secret-sharing and MPC. The

consensus-based ledger mechanism underlying these blockchain systems offers a way to

perform logging, audit and accounting of queries executed against data in distributed

repositories.

(7) Social and economic incentives: For privacy-preserving data sharing to scale and

be adopted by a wide range of stakeholders, social and economic incentives must be

provided, not only for persons or organizations holding “edge data” but also for

infrastructure providers. These infrastructure providers are entities who deliver P2P

network scalability, as well as efficient edge computing services that yield real-time

edge analytics and visibility into the state of data sharing.

The overall goal of any proposed solution should be increased data protection and privacy,

together with scalability, performance and interoperability. In the following, we describe

different evolutionary phases of a solution, where each phases focuses on one or more of the

above key concepts.
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Solution - Phase I “Deployed Blockchain”

The goal here is to explore the use of small number of independent data repositories together

with P2P nodes and blockchain technology such as Hyperledger:

• API-driven query/response controls: The API defined at the data-repository provides a

“hard-wired” query capability. The Querier performs the query by sending a message to

the API at the repository, which in turn results to the Querier. The API itself defines the

type of query accepted, and the granularity of answers being returned.

• Aggregate answers only: The API will return “safe answers” in the form of

aggregate/statistical answers only. This approach conforms to the key principle of never

allowing raw-data to leave the repository.

• Multiple repositories: Multiple data-repositories is envisioned, where each repository

may store only one kind of data (e.g. GPS location) that are constrained through its APIs. 

To the Querier, the nodes on the Networked Collaboration Environment allows Querier

to get access to large number data-repositories – represented as nodes of the P2P

network (i.e. nodes on the blockchain).

• Metadata for discovery: Sharing of data presumes the existence of data is known. A

number of nodes on the Networked Collaboration Environment may take the role of

“metadata directories”, where they can return information regarding the location of

nodes with desired data.

• All access request/response logged: Direct capture of logs into a blockchain is

inefficient and does not scale well. Instead, approaches such as those in Blue Horizon

offer as more promising solution. Each party (the Querier and data repository) tracks

the API calls, and then hashes the logs. Each party must generate the same hash for the

calls, as well as the same hash for data sent/received. These hashes can be written to

the blockchain and can be audited by each party only (for privacy preservation).

• Authorization and Identity: Authorization tokens will be used in conjunction with a

basic blockchain identity, with the focus primarily on authorizations to access a datarepository through the published APIs. The member services capability of systems such

as Hyperledger can begin to be explored in this phase.

Solution - Phase II “Bring Algorithms to the Data”

Building on the previous phase, the goal in this phase is to introduce the use of algorithms or

scripts that are vetted to be safe for a given classification of data. These vetted algorithms can

be signed and published (e.g. at nodes of the Networked Collaboration Environment).

Invocation of one of these published algorithms by a Querier will require all the conditions

stated be fulfilled (e.g. identity of the Querier is verified, target data repositories, authorization

tokens, etc.). The approach build on access APIs from the previous phase, with tighter
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restrictions expressed through vetting of algorithms. The Querier’s choice of algorithm can

recorded on the blockchain, with the returned results being logged and recorded on the

blockchain. Furthermore, a published algorithm can be expressed as a smart contract residing

in one or more of nodes on the Networked Collaboration Environment.

• Query control using vetted algorithms/scripts: Queries are expressed as executable

“algorithms” or scripts. The Querier sends the algorithm to the relevant end-points

located at the data-repositories.

• Flexible queries: In this phase the queries have greater flexibility than the API-driven

approach in Phase I. Subset SQL or Python may be considered as the query/scripts

language.

• Vetting of safe algorithms: Algorithms are first vetted by experts for their safety and

impact to privacy and to the correctness of returned results. Only aggregate/statistical

queries are permitted. Copies of all approved/vetted queries are signed and then stored

at a number of nodes on the Networked Collaboration Environment (participating in

blockchain) for public verification.

• Repositories evaluate and execute algorithms: Each repository must dedicate

computational power (“compute engine”) to execute/evaluate a received query (in the

form of an algorithm) against the available local data. Raw-data itself is never returned.

• Richer data repositories: Each repository is assumed to store richer sets of data of

varying types.

• Authorization & Privacy-preserving Identities: The identity of the Querier and the

repositories need to be preserved from “leakages” of information through methods

such as correlations and others that disclose private information. Basic transaction

identities can be deployed, as part of managing identity, privacy and confidentiality on

the network. Some blockchain systems (e.g. Hyperledger) provide a suitable framework

for “member services” (i.e. user’s core identity and transaction identities).

• Blockchain used for logs and monitoring: A blockchain is used to log all access

request/responses for audit and post-event traffic analysis.

Solution - Phase III “Basic MPC”

This phase introduces more sophisticated cryptographic techniques that support privacypreserving distributed computations over data. Once such technique is secure multi-party

computation (S-MPC). Here an SMPC cryptographic algorithm is used for computation over

data that is stored in plaintext at the repository. A select number of nodes on the blockchain

have SMPC capability, and can participate in Secure MPC computation instances. Focus is on

the performance aspects of a small number of MPC-nodes, including computational
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performance and network bandwidth measurements. An MPC-node may be implemented as an

“overlay” over nodes in a blockchain system. A rudimentary proof-of-MPC-completion maybe

recorded on the underlying blockchain.

• Raw data remains locally at the repositories: The data remains private, and none of the

nodes see each other’s raw data. Furthermore, each data-item is located at its “home”

data repository (i.e. not at a P2P set of nodes).

• Data at rest in plaintext (not encrypted): Data-at-rest a given repository is in plaintext,

and not hidden using secret-sharing encryption. This allows focus to be directed to MPC

algorithms and their performance.

• Simple MPC configuration of known nodes: A small number of repositories (e.g. 3

nodes) will be used to create a group of parties involved in the MPC computation. Each

node in an MPC instance will employ a secure channel (e.g. TLS1.2) to ensure integrity

protection from attacks, and each know the others identity (e.g. via X509 certificate).

• Predefined simple queries: Only simple queries will be addressed, possibly as predefined (template) queries. Complex queries (e.g. inner/outer joins of tables) will be left

for future work.

• Metadata service: Types of data and available simple operations are “advertised” at a

special server, to which Queries can locate relevant repositories.

• Rudimentary Proof-of-MPC-Completion: MPC-nodes need to record the completion of

their MPC-computation on the underlying blockchain, with a matching

verification/validation mechanism. The proof is to be determined, but may consists of

each MPC-node listing its steps and message flows (with other MPC-nodes), and

recording these on the blockchain for later replay/verification. This aspect is relevant for

providing economic incentives nodes to participate within a given MPC computation.

Solution - Phase IV “Full MPC with Secret Sharing”

This phase employs a combination of two sophisticated cryptographic techniques, namely the

Secure MPC technique (from the previous phase) together with data encrypted into pieces (or

“shares”). A minimal “threshold” number of shares are required to re-construct the original

data item. A select number of nodes on the blockchain store “shares” of a data item but never

the complete set of shares, providing resiliency against attacks seeking to recover the data

item. These are called “Shares-node”. The MPC-nodes are now also responsible for collecting

the relevant shares of each data item from the underlying Shares-nodes in the blockchain. Each

Share-node may hold shares corresponding to different data-items, which in turn belong to

different owners. The Querier sends the algorithm/query to a coordinating-node that

represents the Querier to the MPC-nodes.
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• No centralized data-repository: Data-repositories no longer hold any complete data,

but only location of other nodes (shares-node) in the decentralized Networked

Collaboration Environment that hold data (in the form of encrypted data-shares). As the

“owner” of a data-item, the data-repository must perform shares management (i.e.

shares creation, distribution and re-locations).

• Shares distribution, re-collection and management: Each data-repository implements

a “standardized” shares location-management function that support the creation of

shares-coordinates (of all the relevant shares for each data item). The sharescoordinates are then given to the designated MPC-node involved in a given query

instance.

• MPC only nodes: A new category of nodes will be introduced whose purpose is to

participate in and complete an MPC computation instance. This distinction allows for

support of an “outsourcing” model whereby the data repository (who now holds no

actual data) delegates the MPC computation instance to a given MPC-node.

• Shares-based primitive operations: Simple operations (additions and multiplications)

over the encrypted-shares.

• Query-to-primitive translation: Simple translator from subset SQL into the relevant

MPC primitives (additions and operations).

• Authorization for invoking MPC-nodes: The Querier must provide authorization

evidence that it authorized is to request the set of MPC-nodes to collect corresponding

shares and to perform MPC computation on these shares.
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V. Investment Required

R&D investment is needed to implement the solutions suggested herein. In evaluating an R&D

plan, what can we leverage that already exists out there, and what would we need to build.

We recommend that the U.S. Government establish a “Living Lab” to not just test, but actually

deploy, this new paradigm. A Living Lab would prove concept and build confidence towards a

national and international rollout. MIT has employed the Living Lab model in communities as

diverse as Hamburg Germany, the country of Senegal, and Cambridge MA.

We would envision a test starting with 10,000 people, then 100,000+, then 1+ million (roughly

logarithmic proof of concept scaling). It could begin with a neighborhood or small community,

then a town or larger neighborhood, then a midsize city. It could be deployed to a specific

department within the Federal Government. Or, it could be structured on an interest group or

common problem area (“affinity-driven”), such as veterans or federal workers.

Competitions such as the Department of Transportation Smart City Challenge, with a

$50 million prize for the winning proposal, illustrate a viable model for generating a diverse set

of perspectives on the problem and potential solutions.

Criteria for Site Selection

1) Town-scale

2) Proximity to a substantial federal facility

3) End points: consumers, health system, financial system

4) Make interoperable with things that are not new?

5) Advisable: strong local university partner

6) Coordinating “owner” locally

Geographies that meet these characteristics include Boulder CO, Austin TX, Rochester NY,

Hartford CT, and Boston MA. Affinity-driven examples include the Veterans Administration or

the USPS.

A federally administered competition could stimulate innovation much in the same way that

the ARPANet and NSFnet led to the development of the commercial internet.
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Background

The Massachusetts Institute of Technology Connection Science initiative (MIT Connection

Science) hosted a working group session on 11 July 2016 in Cambridge, MA to answer the call

posed by the White House Commission on Cybersecurity, and separately discussions with the

U.S. Secretary of Commerce Penny Pritzker and the European Union’s Vice President Ansip, in

charge of of the Single Digital Market. This document reflects a distillation of the discussion

from the July 11 working group.

Participating were: 

 Alex Pentland (Professor, MIT)

 Irving Wladawsky-Berger (MIT Connection Science Fellow)

 David Shrier (Managing Director, MIT Connection Science)

 Jerry Cuomo (IBM Fellow and Vice President Blockchain Technologies)

 Steve Davis (Senior Consultant, Payments Innovation, MasterCard)

 Michael Frank (Program Director, Blockchain Technologies, IBM)

 Thomas Hardjono (Chief Technology Officer, MIT Connection Science)

 Guerney Hunt (Research Staff Member, IBM)

 Cam Kerry (Visiting Scholar, MIT; formerly General Counsel and Acting Secretary, U.S.

Dept. of Commerce)

 Mark O’Riley (Office of the General Counsel, Government and Regulatory AffairTechnology Policy, IBM)

 Chris Parsons (Vice President Big Data Strategy and Business Development, AT&T)

 Gari Singh (Distinguished Engineer & Blockchain CTO, IBM)

 Anne Shere Wallwork (Senior Counselor for Strategic Policy, Office of Terrorist Financing

and Financial Crimes, U.S. Department of the Treasury)

 Rod Walton (VP Qualcomm)

 Irida Xheneti (Entrepreneur in Residence, MIT Connection Science)

 1 Yampolskiy R et. al. (2008) “Behavioral Biometrics: a survey and classification” Int. J.

Biometrics, Vol. 1, No. 1, 2008

2 World Economic Forum (2009) “The New Deal on Data”)

http://hd.media.mit.edu/wef_globalit.pdf