Venue & metadata

• Journal/Proceedings: Proceedings - 2024 19th European Dependable Computing Conference, EDCC 2024
• Pages: 147 – 154
• Note: Cited by: 3
• Author keywords: Fuzzy Inference; Healthcare; Privacy Risk Assessment; Smart Pervasive Applications

Abstract

The growing diffusion of smart pervasive applications is starting to mine personal privacy: from Internet of Things to Machine Learning, the opportunities for privacy loss are many. As for other concerns involving people and goods as financial, safety and security, researchers and practitioners have defined in time different risk assessment procedures to have repeatable and accurate ways of detecting, quantifying and managing the (possible) source of privacy loss. This paper defines a methodology to deal with privacy risk assessment, overcoming the traditional dichotomy between qualitative (easy to apply) and quantitative (accurate) approaches. The present paper introduces an approach based on fuzzy logic, able to conjugate the benefits of both techniques. The feasibility of the proposed methodology is demonstrated using a healthcare case study. © 2024 IEEE.

Keywords

Fuzzy inference GS Health care GS Fuzzy inferencer GS Healthcare GS Machine-learning GS Personal privacy GS Pervasive applications GS Privacy problems GS Privacy risk assessment GS Privacy risks GS Risks assessments GS Smart pervasive application GS Risk assessment GS

Links & artifacts

DOI Publisher Copy BibTeX Download .bib

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Suggested citation

Barzegar, A., Campanile, L., Marrone, S., Marulli, F., Verde, L., & Mastroianni, M. (2024). Fuzzy-based Severity Evaluation in Privacy Problems: An Application to Healthcare [Conference paper]. Proceedings - 2024 19th European Dependable Computing Conference, EDCC 2024, 147–154. https://doi.org/10.1109/EDCC61798.2024.00037