Estimating g-Leakage via Machine Learning

9 May 2020Marco RomanelliKonstantinos ChatzikokolakisCatuscia PalamidessiPablo Piantanida

This paper considers the problem of estimating the information leakage of a system in the black-box scenario. It is assumed that the system's internals are unknown to the learner, or anyway too complicated to analyze, and the only available information are pairs of input-output data samples, possibly obtained by submitting queries to the system or provided by a third party... (read more)

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