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Data Reconstruction: When You See It and When You Don't

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arxiv 2405.15753 v2 pith:AXT4UZ5E submitted 2024-05-24 cs.CR

classification cs.CR
keywords attacksreconstructiondefinitionsecuritywhatwhenattackformulate
verification ladder T0 review T1 audit T2 compute T3 formal
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We revisit the fundamental question of formally defining what constitutes a reconstruction attack. While often clear from the context, our exploration reveals that a precise definition is much more nuanced than it appears, to the extent that a single all-encompassing definition may not exist. Thus, we employ a different strategy and aim to "sandwich" the concept of reconstruction attacks by addressing two complementing questions: (i) What conditions guarantee that a given system is protected against such attacks? (ii) Under what circumstances does a given attack clearly indicate that a system is not protected? More specifically, * We introduce a new definitional paradigm -- Narcissus Resiliency -- to formulate a security definition for protection against reconstruction attacks. This paradigm has a self-referential nature that enables it to circumvent shortcomings of previously studied notions of security. Furthermore, as a side-effect, we demonstrate that Narcissus resiliency captures as special cases multiple well-studied concepts including differential privacy and other security notions of one-way functions and encryption schemes. * We formulate a link between reconstruction attacks and Kolmogorov complexity. This allows us to put forward a criterion for evaluating when such attacks are convincingly successful.

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Cited by 2 Pith papers

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    A compression-based measurement puts GPT-style model memorization capacity at roughly 3.6 bits per parameter, with membership inference success following a sigmoid in the dataset-to-capacity ratio.

  2. Enforcing Demographic Coherence: A Harms Aware Framework for Reasoning about Private Data Release

    cs.CR 2025-02 conditional novelty 5.0 of 10

    Demographic coherence is a new necessary-condition privacy definition, and the paper proves differential privacy implies it and gives parameter conversions.

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