Current and Future RL’s Contribution to Emerging Network Security

Reinforcement learning is a machine-learning paradigm, which learns the best actions an agent needs to perform to maximize its rewards in a particular environment. Research into RL has been proven to have made a real contribution to the protection of emerging network systems against malware. In this paper, a systematic review of this research was performed in regard to various attacks and an analysis of the trends and future fields of interest for the RL-based research in network security was completed.