Current and future RL's contribution to emerging network security

Authors

C. Feltus

Reference

Procedia Computer Science, vol. 177, pp. 516-521, 2020

Description

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.

Link

doi:10.1016/j.procs.2020.10.071

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