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Privacy Against Brute-Force Inference Attacks
, Article 2019 IEEE International Symposium on Information Theory, ISIT 2019, 7 July 2019 through 12 July 2019 ; Volume 2019-July , 2019 , Pages 637-641 ; 21578095 (ISSN) ; 9781538692912 (ISBN) ; Rassouli, B ; Haddadi, H ; Rabiee, H. R ; Gunduz, D ; The Institute of Electrical and Electronics Engineers, Information Theory Society ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
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