Research on Intelligent Penetration Testing Technology Based on AI
Traditional penetration testing relies on the expertise of engineers,while automatic testing based on known attack patterns and vulnerability databases lacks the flexibility and efficiency to address complex network scenarios.To address these challenges,it proposes an intelligent penetration testing approach empowered by artificial intelligence techniques,based on reinforcement cognition decision-making.By decomposing the penetration attack into various stages and extracting attack units,an iterative system architecture is designed to dynamically generate attack behaviors.To tackle complex network environments,a reinforcement learning-based approach is employed to enable self-evolution capabilities of the attack decision-making agent,achieving efficient intelligent penetration testing.
Penetration testReinforcement cognition and decision-makingAttack decision-making agentSelf-evolution learningIntelligent penetration testing
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