| Title | Privacy Against Brute-Force Inference Attacks |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Osia, Seyed Ali, Rassouli, Borzoo, Haddadi, Hamed, Rabiee, Hamid R., Gündüz, Deniz |
| Conference Name | 2019 IEEE International Symposium on Information Theory (ISIT) |
| Date Published | jul |
| Keywords | brute force attacks, brute-force inference attacks, concave function, concave programming, data privacy, Entropy, f-information, guessing leakage, human factors, linear program, Linear programming, Markov processes, Mutual information, Optimization, piece-wise linear function, piecewise linear techniques, policy-based governance, privacy, privacy-leakage budget, privacy-preserving data release, probability, pubcrawl, sensitive data, utility measure |
| 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. |
| DOI | 10.1109/ISIT.2019.8849291 |
| Citation Key | osia_privacy_2019 |
Privacy Against Brute-Force Inference Attacks