Spyware detection technique based on reinforcement learning
Lysenko, S., Bobrovnikova, K., Popov, P. T. 
ORCID: 0000-0002-3434-5272 , Kharchenko, V. & 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 Science & Technology > Computer Science |
Available under License Creative Commons: Attribution International Public License 4.0.
Download (431kB) | Preview
Export
Downloads
Downloads per month over past year
Metadata
MetadataActions (login required)
Admin Login