Exact Jensen–Shannon Asymptotics for Shuffle Privacy Under Partial Linkability
Exact Jensen–Shannon Asymptotics for Shuffle Privacy Under Partial Linkability
Exact information-theoretic framework for shuffle model privacy under partial linkability — when some messages can be linked via side-channels or timing attacks. Key result: The Anonymity Renewal Theorem shows that without per-round identifier renewal, privacy degrades catastrophically — over a billion-fold in 5 rounds. Includes exact JSD asymptotics, finite-n bounds, Gaussian extension, and design guidelines.
Jensen-Shannon divergence, anonymity, composition theorems, differential privacy, side-channel attacks, privacy amplification, shuffle model, partial linkability, information theory, Gaussian differential privacy
Jensen-Shannon divergence, anonymity, composition theorems, differential privacy, side-channel attacks, privacy amplification, shuffle model, partial linkability, information theory, Gaussian differential privacy
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