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

Author

Listed:
  • Dimitrios Papamartzivanos

    (R&D Department, Ubitech Ltd., 11632 Athens, Greece)

  • Sofia Anna Menesidou

    (R&D Department, Ubitech Ltd., 11632 Athens, Greece)

  • Panagiotis Gouvas

    (R&D Department, Ubitech Ltd., 11632 Athens, Greece)

  • Thanassis Giannetsos

    (DTU Compute, Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Lyngby, Denmark)

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.

Suggested Citation

  • Dimitrios Papamartzivanos & Sofia Anna Menesidou & Panagiotis Gouvas & Thanassis Giannetsos, 2021. "A Perfect Match: Converging and Automating Privacy and Security Impact Assessment On-the-Fly," Future Internet, MDPI, vol. 13(2), pages 1-34, January.
  • Handle: RePEc:gam:jftint:v:13:y:2021:i:2:p:30-:d:487796
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    References listed on IDEAS

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    1. Jane Henriksen-Bulmer & Shamal Faily & Sheridan Jeary, 2020. "DPIA in Context: Applying DPIA to Assess Privacy Risks of Cyber Physical Systems," Future Internet, MDPI, vol. 12(5), pages 1-23, May.
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    Cited by:

    1. Weizhi Meng & Thanassis Giannetsos & Christian D. Jensen, 2022. "Information and Future Internet Security, Trust and Privacy," Future Internet, MDPI, vol. 14(12), pages 1-2, December.
    2. Sanaa Kaddoura & Ramzi A. Haraty & Karam Al Kontar & Omar Alfandi, 2021. "A Parallelized Database Damage Assessment Approach after Cyberattack for Healthcare Systems," Future Internet, MDPI, vol. 13(4), pages 1-18, March.

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