Autonomous Cyber

Autonomous cyber defense research focuses on developing AI-powered systems capable of automatically detecting and responding to cyberattacks, reducing reliance on human experts. Current efforts concentrate on applying reinforcement learning (RL), particularly multi-agent RL and deep RL, often coupled with techniques like Bayesian optimization and causal modeling, to create adaptable and efficient defense strategies within simulated and real-world environments. This field is crucial for mitigating the increasing sophistication and scale of cyber threats, offering the potential to significantly improve network security and resilience across various sectors.