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Spyware detection technique based on reinforcement learning

Lysenko, S., Bobrovnikova, K., Popov, P. T. ORCID: 0000-0002-3434-5272, Kharchenko, V. and Medzatyi, D. (2020). Spyware detection technique based on reinforcement learning. CEUR Workshop Proceedings, 2623, pp. 307-316.

Abstract

Analysis of the antivirus technologies, showed that they are not able to detect new spyware with high efficiency, which significantly reduces the reliability and efficiency of its identification. Techniques based on heuristic analysis have a high rate of false positives. The paper presents a new technique for the spyware detection method in computer systems that provides a principle of proactivity and is based on mechanisms machine learning with the reinforce-mentlearning. The suggested method of spyware detection is based on software behavior analysis in computer systems. The suggested method involves the computer systems monitoring concerning the software, operates with the behavior.

Publication Type: Article
Additional Information: Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Publisher Keywords: Spyware, Malware, Cyberattack, API, Machine Learning, Reinforcement Learning, Network, Cybersecurity, Computer system, Host, Detection
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Mathematics, Computer Science & Engineering > Computer Science
Date Deposited: 26 Aug 2020 11:45
URI: https://openaccess.city.ac.uk/id/eprint/24815
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