Q-Learning Approach Applied to Network Security

Network security and intrusion detection and response (IDR) are necessary issues nowadays. Enhancing our cyber defense by discovering advanced machine learning models, such as reinforcement learning and Q-learning, is a crucial security measure. This study proposes a novel intrusion response method by implementing an off-policy Q-learning approach. We test the validity of our model by conducting a goodness-of-fit analysis and proving its efficiency. By performing sensitivity analysis, we prove that it is possible to protect our network successfully and establish an immediate response mechanism that could be successfully implemented in intrusion response (IR) systems.