Year: 2020
Type: conference-paper
Study design: Systematic Review
Abstract: 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.
Source: Procedia Computer Science
Author: Christophe Feltus
Institution: Luxembourg Institute of Science and Technology
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W3098999489