Speaker: Srini Devadas
Location: Soda 430-438, Woz Lounge
Date: June 30, 2023
Time: 12-1pm PST
Title: AC Privacy: Automatic Privacy Measurement and Control of Data Processing
Abstract: We propose and study a new privacy definition, termed Probably Approximately Correct (PAC) Privacy. PAC Privacy characterizes the information-theoretic hardness to recover sensitive data given arbitrary information disclosure/leakage during/after any processing. Unlike the classic cryptographic definition and Differential Privacy (DP), which consider the adversarial (input-independent) worst case, PAC Privacy is a simulatable metric that quantifies the instance-based impossibility of inference. A fully automatic analysis and proof generation framework is proposed: security parameters can be produced with arbitrarily high confidence via Monte-Carlo simulation for any black-box data processing oracle. On the utility side, the magnitude of (necessary) perturbation required in PAC Privacy is not lower bounded by Θ(√d) for a d-dimensional release but could be O(1) for many practical data processing tasks, which is in contrast to the input-independent worst-case information-theoretic lower bound. We discuss applications of PAC Privacy to statistical data processing tasks.
Bio: Srini Devadas, is a Professor of Electrical Engineering and Computer Science at MIT in the Computer Science and Artificial Intelligence Laboratory (CSAIL). Srini belongs to the Computation Structures Group. His current research interests are primarily in the areas of applied cryptography, computer security and computer architecture.