Preserving Privacy and Fidelity via Ehrhart Theory
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© 2018 IEEE. We consider the problem of designing a database sanitization mechanism (DSM) that minimizes, in the expected sense, the mathbb L- 1 -distortion between the histograms of original and sanitized databases, while being Θ -differentially private (DP). The expected mathbb L- 1 -distortion of a corresponding optimal Θ- DP DSM provides for an important utility-privacy trade-off. This problem reduces to a prohibitively complex linear program (LP). Using tools from Ehrhart theory, analytic combinatorics and LP theory, we solve this problem and thereby provide a simple closed form computable expression characterizing this trade-off.
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2018 IEEE International Symposium on Information Theory (ISIT)
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2018 IEEE International Symposium on Information Theory (ISIT)
author list (cited authors)
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Padakandla, A., Kumar, P. R., & Szpankowski, W
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Padakandla, Arun||Kumar, PR||Szpankowski, Wojciech
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International Standard Book Number (ISBN) 13
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