Title: A new method for behavioural-based malware detection using reinforcement learning

Authors: Sepideh Mohammadkhani; Mansour Esmaeilpour

Addresses: Computer Engineering Department, Hamedan Branch, Islamic Azad University, Hamedan, Iran ' Computer Engineering Department, Hamedan Branch, Islamic Azad University, Hamedan, Iran

Abstract: Malware is - the abbreviation for malicious software - a comprehensive term for software that is deliberately created to perform an unauthorised and often harmful function. Viruses, backdoors, key-loggers, Trojans, password thieves' software, spyware, adwares are number of malware samples. Previously, calling something a virus or Trojan was enough. However, methods of contamination are developed, the term virus and other malware definition was not satisfactory for all types of malicious programs. This research focus on clustering the malware according to the malware features. To avoid the dangers of malware, some applications have been created to track them down. This paper presents a new method for detection of malware using reinforcement learning. The result demonstrates that the proposed method can detect the malware more accurate.

Keywords: antivirus; AVS; malware; reinforcement learning.

DOI: 10.1504/IJDMMM.2018.095372

International Journal of Data Mining, Modelling and Management, 2018 Vol.10 No.4, pp.314 - 330

Accepted: 31 Jan 2018
Published online: 04 Sep 2018 *

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