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Beyond CAGE: Investigating Generalization of Learned Autonomous Network Defense Policies
Advancements in reinforcement learning (RL) have inspired new directions in intelligent automation of network defense.
Towards Causal Models for Adversary Distractions
Automated adversary emulation is becoming an indispensable tool of network security operators in testing and evaluating their cyber defenses.
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