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EPIC: a Methodology for Evaluating Privacy Violation Risk in Cybersecurity Systems
Sergio Mascetti(a),(*), Nadia Metoui(a), Andrea Lanzi(a), Claudio Bettini(a)
Transactions on Data Privacy 11:3 (2018) 239 - 277
Abstract, PDF
(a) Università degli Studi di Milano, Department of Computer Science.
e-mail:sergio.mascetti @unimi.it; nadia.metoui @unimi.it; andrea.lanzi @unimi.it; claudio.bettini @unimi.it
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Abstract
Cybersecurity Systems (CSSs) play a fundamental role in guaranteeing data confidentiality, integrity, and availability. However, while processing data, CSSs can intentionally or unintentionally expose personal information to people that can misuse them. For this reason, privacy implications of a CSS should be carefully evaluated. This is a challenging task mainly because modern CSSs have complex architectures and components. Moreover, data processed by CSSs can be exposed to different actors, both internal and external to the organization. This contribution presents a methodology, called EPIC, that is specifically designed to evaluate privacy violation risks in cybersecurity systems. Differently, from other general purpose guidelines, EPIC is an operational methodology aimed at guiding security and privacy experts with step-by-step instructions from modeling data exposure in the CSS to the systematical identification of privacy threats and evaluation of their associated privacy violation risk. This contribution also shows the application of the EPIC methodology to the use case of a large academic organization CSS protecting over 15, 000 hosts.
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