Conference Proceedings

Measuring Information Leakage in Non-stochastic Brute-Force Guessing

Farhad Farokhi, Ni Ding

2020 IEEE Information Theory Workshop (ITW) | IEEE | Published : 2021

Abstract

We propose an operational measure of information leakage in a non-stochastic setting to formalize privacy against a brute-force guessing adversary. We use uncertain variables, non-probabilistic counterparts of random variables, to construct a guessing framework in which an adversary is interested in determining private information based on uncertain reports. We consider brute-force trial-and-error guessing in which an adversary can potentially check all the possibilities of the private information that are compatible with the available outputs to find the actual private realization. The ratio of the worst-case number of guesses for the adversary in the presence of the output and in the absen..

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University of Melbourne Researchers

Grants

Funding Acknowledgements

The work of F. Farokhi is funded by the Melbourne School of Engineering. Aspects of this work was done while F. Farokhi was also affiliated with CSIRO's Data61. The work of Ni Ding is funded by the Doreen Thomas Postdoctoral Fellowship at the University of Melbourne.