Automated Cyber Defense with Generalizable Graph-Based Reinforcement Learning Agents

Deep reinforcement learning RL is emerging as a viable strategy for automated cyber defense ACD. The traditional RL approach represents networks as a list of computers in various states of safety or threat. Unfortunately, these models are forced to overfit to specific network topologies, renderin...

MAI-2024-0059

Multimodal Large Language Models MLLMs operating within multi-agent environments are susceptible to a sophisticated attack known as "infectious jailbreak." This vulnerability is triggered by the introduction of a single adversarial image into the memory of one agent, which can rapidly propagate...