RLShield: Practical Multi-Agent RL for Financial Cyber Defense with Attack-Surface MDPs and Real-Time Response Orchestration

Researchers have developed RLShield, a multi-agent reinforcement learning system designed to automate cyber defense in financial institutions. The system uses AI to coordinate real-time responses across multiple assets and services during cyberattacks, balancing containment speed with operational costs and business disruption.