Gaoyi Chen
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The paper introduces Metric-Normalized Posterior Leakage (mPL), an attacker-aligned measure that provides a practical, certifiable privacy guarantee for machine learning systems consumed under joint observation, addressing shortcomings of traditional differential privacy.
The paper proposes Context-aware Metric Differential Privacy (C-mDP), a framework that improves vehicle location privacy by modeling temporal dependencies, achieving higher data utility than standard methods.
Papers
Context-Aware Metric Differential Privacy for Vehicle Trajectory Data
The paper proposes Context-aware Metric Differential Privacy (C-mDP), a framework that improves vehicle location privacy by modeling temporal dependencies, achieving higher data utility than standard…