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Privacy Against Brute-Force Inference Attacks

TitlePrivacy Against Brute-Force Inference Attacks
Publication TypeConference Paper
Year of Publication2019
AuthorsOsia, S. A., H. Haddadi, and H. R. Rabiee
Conference NameIEEE International Symposium on Information Theory
Date Published07/07
PublisherIEEE
Conference LocationParis, France
AbstractPrivacy-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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