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Reinforcement Learning Approaches in Cyber Security
Abstract
Reinforcement learning (RL) allows defense mechanisms to adapt to changing threats and has shown promise in tackling cyber security issues. This study presents a thorough introduction which includes foundations, uses, and difficulties to RL in cyber security. The efficacy of RL in making decisions is also emphasized in the introduction. Then the foundation for comprehending RL's use in cyber security, the fundamentals of the technology, and algorithm classifications is clarified. The study then delves into a number of RL applications in cyber security. Then a number of RL applications in cyber security and issues in RL is discussed. Along with prospects for improving cyber security safeguards through the application of RL methodologies, to successfully manage increasing cyber threats, future research directions are proposed with the integration of blockchain technology and generative adversarial networks (GANs). This work emphasizes the importance of RL in supporting cyber security and research to improve cyber defenses.
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