Bayesian Perspective on Memorization and Reconstruction
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866918038303932416 |
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| author | Kaplan, Haim Mansour, Yishay Nissim, Kobbi Stemmer, Uri |
| author_facet | Kaplan, Haim Mansour, Yishay Nissim, Kobbi Stemmer, Uri |
| contents | We introduce a new Bayesian perspective on the concept of data reconstruction, and leverage this viewpoint to propose a new security definition that, in certain settings, provably prevents reconstruction attacks. We use our paradigm to shed new light on one of the most notorious attacks in the privacy and memorization literature - fingerprinting code attacks (FPC). We argue that these attacks are really a form of membership inference attacks, rather than reconstruction attacks. Furthermore, we show that if the goal is solely to prevent reconstruction (but not membership inference), then in some cases the impossibility results derived from FPC no longer apply. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_23658 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Bayesian Perspective on Memorization and Reconstruction Kaplan, Haim Mansour, Yishay Nissim, Kobbi Stemmer, Uri Cryptography and Security Machine Learning We introduce a new Bayesian perspective on the concept of data reconstruction, and leverage this viewpoint to propose a new security definition that, in certain settings, provably prevents reconstruction attacks. We use our paradigm to shed new light on one of the most notorious attacks in the privacy and memorization literature - fingerprinting code attacks (FPC). We argue that these attacks are really a form of membership inference attacks, rather than reconstruction attacks. Furthermore, we show that if the goal is solely to prevent reconstruction (but not membership inference), then in some cases the impossibility results derived from FPC no longer apply. |
| title | Bayesian Perspective on Memorization and Reconstruction |
| topic | Cryptography and Security Machine Learning |
| url | https://arxiv.org/abs/2505.23658 |