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2020-09-04
Osia, Seyed Ali, Rassouli, Borzoo, Haddadi, Hamed, Rabiee, Hamid R., Gündüz, Deniz.  2019.  Privacy Against Brute-Force Inference Attacks. 2019 IEEE International Symposium on Information Theory (ISIT). :637—641.
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.