Privacy Against Brute-Force Inference Attacks

Seyed Ali Osia; Borzoo Rassouli; Hamed Haddadi; Hamid R. Rabiee; Deniz Gündüz

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arXiv · 1902.00329

Privacy Against Brute-Force Inference Attacks

Seyed Ali Osia·Borzoo Rassouli·Hamed Haddadi·Hamid R. Rabiee·Deniz Gündüz

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Abstract

Privacy-preserving data release is about disclosing information about useful data while retaining the privacy of sensitive data. Assuming that the sensitive data is threatened by a brute-force adversary, we define Guessing Leakage as a measure of privacy, based on the concept of guessing. After investigating the properties of this measure, we derive the optimal utility-privacy trade-off via a linear program with any $f$-information adopted as the utility measure, and show that the optimal utility is a concave and piece-wise linear function of the privacy-leakage budget.

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Seyed Ali Osia, Borzoo Rassouli, Hamed Haddadi, Hamid R. Rabiee, Deniz Gündüz. 2019-02-01. Privacy Against Brute-Force Inference Attacks. https://arxiv.org/abs/1902.00329

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