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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2411.18531 |
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| _version_ | 1866910718840799232 |
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| author | Wang, Shuaiqi Lin, Zinan Fanti, Giulia |
| author_facet | Wang, Shuaiqi Lin, Zinan Fanti, Giulia |
| contents | We introduce a privacy measure called statistic maximal leakage that quantifies how much a privacy mechanism leaks about a specific secret, relative to the adversary's prior information about that secret. Statistic maximal leakage is an extension of the well-known maximal leakage. Unlike maximal leakage, which protects an arbitrary, unknown secret, statistic maximal leakage protects a single, known secret. We show that statistic maximal leakage satisfies composition and post-processing properties. Additionally, we show how to efficiently compute it in the special case of deterministic data release mechanisms. We analyze two important mechanisms under statistic maximal leakage: the quantization mechanism and randomized response. We show theoretically and empirically that the quantization mechanism achieves better privacy-utility tradeoffs in the settings we study. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_18531 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Statistic Maximal Leakage Wang, Shuaiqi Lin, Zinan Fanti, Giulia Information Theory We introduce a privacy measure called statistic maximal leakage that quantifies how much a privacy mechanism leaks about a specific secret, relative to the adversary's prior information about that secret. Statistic maximal leakage is an extension of the well-known maximal leakage. Unlike maximal leakage, which protects an arbitrary, unknown secret, statistic maximal leakage protects a single, known secret. We show that statistic maximal leakage satisfies composition and post-processing properties. Additionally, we show how to efficiently compute it in the special case of deterministic data release mechanisms. We analyze two important mechanisms under statistic maximal leakage: the quantization mechanism and randomized response. We show theoretically and empirically that the quantization mechanism achieves better privacy-utility tradeoffs in the settings we study. |
| title | Statistic Maximal Leakage |
| topic | Information Theory |
| url | https://arxiv.org/abs/2411.18531 |