An efficient reinforcement learning-based Botnet detection approach
Mohammad Alauthman, Nauman Aslam, Mouhammd Sharari Alkasassbeh, Suleman Khan, Ahmad Al–Qerem, Kim‐Kwang Raymond Choo · Journal of Network and Computer Applications · 2019
The use of bot malware and botnets as a tool to facilitate other malicious cyber activities (e.g. distributed denial of service attacks , dissemination of malware and spam , and click fraud). However, detection of botnets , particularly peer-to-peer (P2P) botnets, is challenging. Hence, in this paper we propose a sophisticated traffic reduction mechanism, integrated with a reinforcement learning technique . We then evaluate the proposed approach using real-world network traffic, and achieve a detection rate of 98.3%. The approach also achieves a relatively low false positive rate (i.e. 0.012%).