De-anonymization of health data: a survey of practical attacks, vulnerabilities and challenges
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Published Version
Date
2025
Authors
Aguelal , Hamza
Palmieri, Paolo
Journal Title
Journal ISSN
Volume Title
Publisher
SCITEPRESS
Published Version
Abstract
Health data ranks among the most sensitive personal information disclosing serious details about individuals. Although anonymization is used, vulnerabilities persist, leading to de-anonymization and privacy risks highlighted by regulations like the General Data Protection Regulation (GDPR). This survey examines de-anonymization attacks on health datasets, focusing on methodologies employed, data targeted, and the effectiveness of current anonymization practices. Unlike previous surveys that lack consensus on essential empirical questions, we provide a comprehensive summary of practical attacks, offering a more logical perspective on real-world risk. Our investigation systematically categorizes these practical attacks, revealing insights into suc cess rates, generality and reproducibility, new analytics used, and the specific vulnerabilities they exploit. The study covers health-related datasets, including medical records, genomic data, electrocardiograms (ECGs), and neuroimaging, highlighting the need for more robust anonymization. Significant challenges remain in the literature despite existing reviews. We advocate for stronger data safeness by improving anonymization methods and advancing research on de-anonymization and assessment within healthcare.
Description
Keywords
Health data , Anonymization , De-anonymization attacks
Citation
Aguelal, H. and Palmieri, P. (2025) 'De-anonymization of health data: a survey of practical attacks, vulnerabilities and challenges', Proceedings of the 11th International Conference on Information Systems Security and Privacy (ICISSP 2025), Porto, Portugal, 20-22 February, Volume 2, pp. 595-606. https://doi.org/10.5220/0013274200003899