# A Perfect Match: Converging and Automating Privacy and Security Impact Assessment On-the-Fly
## 4 APSIA Conceptual Architecture and Building Blocks
### Privacy Impact Scoring System
#### 4.3.2 Privacy Impact  
The Privacy impact reflects the consequences an exploited vulnerability may have on a data subject's privacy. As have been already stated, one of the current scoring systems shortfalls is the lack of a risk scoring system that adequately considers the context of the environment for identified vulnerabilities. Thus, the utilisation of a scoring system that focuses exclusively on the impact on CIA metrics, fails to consider the operational ramifications imposed to the affected organisation. To address this issue, the proposed scoring system incorporates the privacy impact as contributing factor, to extrapolate the vulnerability exploitation impact to the privacy dimension. The privacy impact itself consists three components, namely, (a) the level of impact on the fundamental rights and freedoms of the individuals, (b) the scope of impact to the data processing activities, and (c) the type (i.e., sensitivity) of the processed data. The aforementioned components and their contribution in the scoring formula are described in the following sections. \[\textit{Privacy Impact}=\textit{Level of Impact}+\textit{Scope of Impact}+\textit{Data type} \tag{3}\]  
A. Level of Impact  
The level of impact aims to assess the impact on the fundamental rights and freedoms of the individuals, resulting from the possible loss of security of the personal data. Four levels of impact are considered (Low, Medium, High, Very High) as shown in Table 2, following the taxonomy proposed by ENISA for the personal data processing [49] considering also the case where there is no impact to the rights and freedoms of the individual. As can be inferred by the taxonomy proposed by ENISA, the lowest level of impact considers minor consequences on individuals, while at the highest level, the affected individuals may suffer significant of even irreversible consequences. Although this taxonomy has been adopted on ENISA's tool [31] for evaluating the level of risk of personal data processing operations, the determination of the appropriate value relies explicitly on the situational awareness and the domain experience of the assessor. In the context of the scoring formula of this work, the exact level of impact is determined based on a systematic approach which considers the type of the vulnerability which targets an asset, as well as the importance of the latter in data processing activities of the organisation. In this way, the scoring system considers the nature of the vulnerability which targets an asset and the privacy-oriented business value of it. **Vulnerability type:** In order to identify the type of the vulnerability, we adopted the taxonomy used by CVEdetails [50] online vulnerability database. CVEdetails provides an easy to access interface to CVE vulnerability data. Vulnerabilities are categorised based on vendors, products, and versions. CVE vulnerability data are taken from National Vulnerability Database (NVD) [40] xml feeds provided by NIST. Additional data from several sources like exploits from exploit-db [51], vendor statements and additional vendor supplied data, Metasploit modules are also published in addition to NVD CVE data. Hence, CVEdetails is a database which enriches the basic CVEs with additional metadata and offers a classification that reveals 13 type of the vulnerabilities, as can be seen below. The type of a vulnerability is a parameter of significant importance that enhances the situational awareness of a security defender when it comes to the prioritisation of actions for mitigating cyber risks. The same applies in the case where the defender must make decisions considering the data protection and the user privacy. For instance, vulnerabilities of the Gain Information or the SQL Injection categories, can have a greater impact on users' privacy in contrast to a Denial of Service, which mainly affect the availability of a source.