A general framework defends any shuffle-DP protocol against poisoning attacks on union-preserving queries, retaining asymptotically equivalent error without attacks and only polylogarithmic increase with constant attackers.
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PostRI computes randomization intervals after differentially private median estimation, delivering 14-850% higher median utility than prior methods while keeping narrow intervals.
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Defense against Poisoning Attacks under Shuffle-DP
A general framework defends any shuffle-DP protocol against poisoning attacks on union-preserving queries, retaining asymptotically equivalent error without attacks and only polylogarithmic increase with constant attackers.
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Interpreting the Error of Differentially Private Median Queries through Randomization Intervals
PostRI computes randomization intervals after differentially private median estimation, delivering 14-850% higher median utility than prior methods while keeping narrow intervals.