Privacy Against Brute-Force Inference Attacks
Information Theory
2019-02-04 v1 Cryptography and Security
math.IT
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 -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.
Keywords
Cite
@article{arxiv.1902.00329,
title = {Privacy Against Brute-Force Inference Attacks},
author = {Seyed Ali Osia and Borzoo Rassouli and Hamed Haddadi and Hamid R. Rabiee and Deniz Gündüz},
journal= {arXiv preprint arXiv:1902.00329},
year = {2019}
}