Real-Time Adversarial Defense via Buffer-Aware Reinforcement Learning
Real-time systems built on deep neural networks cannot afford a single, fixed adversarial defense: maximal purification of every input exceeds latency and compute budgets, while no defense leaves the system exposed. We present ATDS-BARL, an Adaptive Tiered Defense System in which a Proximal Policy Optimization (PPO) ag...