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Tag: security

  • Hierarchical Multi-agent Reinforcement Learning for Cyber Network Defense

    Hierarchical Multi-agent Reinforcement Learning for Cyber Network Defense

    Abstract: Recent advances in multi-agent reinforcement learning (MARL) have created opportunities to solve complex real-world tasks. Cybersecurity is a notable application area, where defending networks against sophisticated adversaries remains a challenging task typically performed by teams of security operators. In this work, we explore novel MARL strategies for building autonomous cyber network defenses that address…

  • Adversarial Inception for Bounded Backdoor Poisoning in Deep Reinforcement Learning

    Adversarial Inception for Bounded Backdoor Poisoning in Deep Reinforcement Learning

    Abstract: Recent works have demonstrated the vulnerability of Deep Reinforcement Learning (DRL) algorithms against training-time, backdoor poisoning attacks. These attacks induce pre-determined, adversarial behavior in the agent upon observing a fixed trigger during deployment while allowing the agent to solve its intended task during training. Prior attacks rely on arbitrarily large perturbations to the agent’s…