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Knowing the attribute dependencies within a population lets attackers infer membership with surprising accuracy, even against statistical releases designed to protect privacy.
Oblivious differential privacy can achieve exponential accuracy under continual observation, while adaptive differential privacy provably fails after a constant number of releases, revealing a stark separation.
