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A Perfect Match: Converging and Automating Privacy and Security Impact Assessment On-the-Fly

Authors: Dimitrios Papamartzivanos; Sofia-Anna Menesidou; Panagiotis Gouvas; Thanassis Giannetsos;

A Perfect Match: Converging and Automating Privacy and Security Impact Assessment On-the-Fly

Abstract

As the upsurge of information and communication technologies has become the foundation of all modern application domains, fueled by the unprecedented amount of data being processed and exchanged, besides security concerns, there are also pressing privacy considerations that come into play. Compounding this issue, there is currently a documented gap between the cybersecurity and privacy risk assessment (RA) avenues, which are treated as distinct management processes and capitalise on rather rigid and make-like approaches. In this paper, we aim to combine the best of both worlds by proposing the APSIA (Automated Privacy and Security Impact Assessment) methodology, which stands for Automated Privacy and Security Impact Assessment. APSIA is powered by the use of interdependency graph models and data processing flows used to create a digital reflection of the cyber-physical environment of an organisation. Along with this model, we present a novel and extensible privacy risk scoring system for quantifying the privacy impact triggered by the identified vulnerabilities of the ICT infrastructure of an organisation. We provide a prototype implementation and demonstrate its applicability and efficacy through a specific case study in the context of a heavily regulated sector (i.e., assistive healthcare domain) where strict security and privacy considerations are not only expected but mandated so as to better showcase the beneficial characteristics of APSIA. Our approach can complement any existing security-based RA tool and provide the means to conduct an enhanced, dynamic and generic assessment as an integral part of an iterative and unified risk assessment process on-the-fly. Based on our findings, we posit open issues and challenges, and discuss possible ways to address them, so that such holistic security and privacy mechanisms can reach their full potential towards solving this conundrum.

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Denmark
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Keywords

privacy scoring system, General Data Protection Regulatio, Privacy quantification, Information technology, healthcare data privacy, Privacy Impact Assessment, T58.5-58.64, Privacy scoring syste, privacy quantification, Privacy Impact Assessmen, Privacy Impact Assessment; General Data Protection Regulation; privacy scoring system; privacy quantification; healthcare data privacy, Healthcare data privacy, General Data Protection Regulation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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