Intrusion Response Decision-making Method Based on Reinforcement Learning

Abstract

Aimed at the poor adaptability of intrusion response decision nowadays, this paper proposes an adaptive intrusion response decision method based on reinforcement learning. Based on reinforcement learning, propose an attack pattern matching layer to optimize the learning effect. Based on Softmax, the defense strategies selection method is designed to solve the exploration-utilization problem. Based on the voting mechanism, a multi-response purpose strategy evaluation method is designed. Based on the above, an adaptive intrusion response decision-making algorithm based on reinforcement learning is proposed. The simulation results show that the algorithm has good adaptability, and can make targeted responses to different abilities attackers.