# 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  
As mentioned in the introduction of this work, the current privacy risk assessment methods and tools perform the risk assessment by ignoring the cybersecurity state of the underlined infrastructure. In fact, the reported tools in Section 2 base the assessment on documenting the organisation's procedures and the definition of the final risk depends completely on the perception of the administrator. In fact, 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 [46]. This can lead the organisations to improperly prioritise their mitigation efforts. In the frame of our method and tool, the context is the data subject's privacy and our aim is to provide a formula which considers the peculiarities of the organisation's data processing procedures along with its cyber security state.  
Current methods for analysing identified cyber vulnerabilities of traditional information technology systems tend to focus on the impact to systems' CIA triad to discern end-user risks. Although this approach is sufficient for evaluating traditional information technology systems, it fails to consider the operational ramifications for complex systems-of-systems. Thus, there is a need for a Risk Scoring System that provides the means to characterize identified vulnerabilities and numerically score the effect that a potential exploitation of a vulnerability may have on users' privacy.  
To address this limitation, approach quantifies the privacy risk based on a generic and extensible scoring system, which takes into consideration, not only the vulnerability score per se, but also the potential impact to patient's privacy. This scoring system will be used to measure the privacy impact of the data processing activities of an organisation, given the vulnerabilities of the supporting assets. Given that GDPR compliance is necessary for organisations, this scoring system can contribute towards measuring the degree of GDPR compliance.  
The developed scoring system incorporates two primary factors, which are used to calculate a Total Score: (i) Vulnerability Characterization, and (ii) Privacy Impact. On the one hand, the vulnerability characterization refers to the details and the severity of the vulnerability, which in turn may threaten a user's privacy. On the other, the Privacy impact is based on three contributing factors, namely:  
* the level of impact on the fundamental rights and freedoms of the individuals
* the scope of impact to the data processing activities
* the type (i.e., sensitivity) of the processed data  
By combining these two elements, the scoring system provides the mean for reflecting the severity of an identified vulnerability in the context of users' privacy.  
In the context of our work, the vulnerability score is based on the Common Vulnerability Scoring System (CVSS) [47], where a value from 0 to 10 is assigned to the identified vulnerability, following the system's scoring formulas. However, the determination of the privacy impact is based on the aforementioned contributing factors, which will be explained in detail in Section 4.3.2.  
The final score and the contributing factors follow the structure depicted in Figure 5. While the scoring algorithm combines these two factors, it treats the impact as the leading factor for the final assessment. Indeed, it uses a weighted scale to focus on the impact to users' privacy, while incorporating the vulnerability score. The scores are evaluated on a 0 to 10 scale, with higher numbers indicating more severe ratings. It must be stated that the exact value of the weights is a parameter that can be adjusted accordingly, given the preferences and the domain knowledge of experts of the organisation. The weighted scale formula is given in Equation (1).  
\[\textit{Privacy Score}=(\textit{Vulnerability Characterization}+2\times\textit{ Privacy Impact})/3 \tag{1}\]