Summary

Framework using Reinforcement Learning and Multi-Armed Bandits to dynamically optimize privacy-preserving defense mechanisms. Adapts to different datasets, inference attacks, privacy defenses, utility functions, and hyperparameters. PrivaGuard component selects and applies defense actions while environment evaluates privacy and utility.