DynPen: Automated Penetration Testing in Dynamic Network Scenarios Using Deep Reinforcement Learning
Abstract: Penetration testing, a crucial industrial practice for securing networked systems and infrastructures, has traditionally depended on the extensive expertise of human professionals.
Abstract: Object detection in real-world deployment often suffers from severe performance degradation due to domain shifts between training and test environments, such as drastic variations in style ...
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