Name
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. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ISIT.2019.8849291 | 2019 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT) |
Field | DocType | Volume |
Mathematical optimization,Inference,Brute force,Linear programming,Adversary,Linear function,Mathematics | Journal | abs/1902.00329 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seyed Ali Ossia | 1 | 23 | 2.09 |
| Borzoo Rassouli | 2 | 98 | 11.32 |
| Hamed Haddadi | 3 | 223 | 22.94 |
| Hamid R. Rabiee | 4 | 336 | 41.77 |
| Deniz Gündüz | 5 | 4 | 2.08 |