Balancing the privacy-utility trade-off: How to draw reliable conclusions from private data
Researchers formalise the privacy-utility trade-off after declaring absolute anonymization a "broken promise," offering a framework relevant to GDPR-era data governance.
Summary written by editorial AI · Source link below
arXiv:2603.12753v2 Announce Type: replace-cross Abstract: Absolute anonymization, conceived as an irreversible transformation preventing re-identification and sensitive value disclosure, has proven to be a broken promise. Modern data protection must therefore shift toward a privacy-utility trade-off grounded in risk mitigation. Differential Privacy (DP) offers a rigorous mathematical framework for balancing quantified disclosure risk with analytical usefulness. Nevertheless, widespread adoption
Editorial Analysis
Enterprises relying on anonymization to satisfy GDPR may need to reassess their approach as research confirms re-identification remains feasible under common techniques.
Audit current data-anonymization methods against modern re-identification attacks and consider differential-privacy alternatives.
Academic research confirms that traditional anonymization does not guarantee GDPR compliance, signalling potential regulatory exposure.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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