ARTA: Adaptive Reinforcement-Learning-Based Throttling Agent for RowHammer Vulnerabilities (opens in new tab)  💾DRAM Internals  Content type: Academic

RowHammer vulnerability continues to intensify with DRAM scaling, reducing the activation threshold needed to induce bitflips and rendering existing defenses such as TRR, ECC, and refresh-based mechanisms vulnerable to sophisticated multi-bank hammering patterns. This work presents ARTA, a lightweight reinforcement-learning-based throttling mechanism that detects and suppresses RowHammer activity by monitoring fine-grained memory access behavior...