Unified Framework for Adversary-Aware Differential Privacy Bounds
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A Unified Framework for Adversary-Aware Differential Privacy Bounds
arXiv:2507.08158v2 Announce Type: replace Abstract: Differential Privacy (DP) bounds the privacy leakage of a mechanism against worst-case membership inference, but the precise tradeoff between complex adversarial models and DP protections remains poorly understood. In this paper, we present a unified framework that generalizes the patchwork of existing bounds across membership inference, attribute inference, and data reconstruction attacks. Crucially, our framework is the first to evaluate...