IIARD International Institute of Academic Research and Development

International Journal of Engineering and Modern Technology (IJEMT )

E-ISSN 2504-8848
P-ISSN 2695-2149
VOL. 9 NO. 1 2023

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On Development of Malware Threats Detection and Prevention using artificial Immune System and Machine Learning Algorithm

Ubochi Chinyere., Igbe C.M., Amanze B.C., Agbakwuru O.A & Agbasonu V.C

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Abstract

Malare threats detection and prevention using artificial immune system and machine learning is a research work aimed at developing a system to enhance the security of the computer systems. With the rapid technological advancement, security has become a major issue due to the increase in malware activity that poses a serious threat to the security and safety of both computer systems and stakeholders. A set of malicious programming code, scripts, active content or intrusive software that is designed to destroy intended computer systems and programs is referred to as malware. According to a study, naive users are unable to distinguish between malicious and genuine applications. Thus, computer systems should be designed to detect malicious activities towards protecting the system from threats. A number of algorithms are available to detect malware activities by utilizing novel concepts including Artificial Intelligence, Machine Learning, and Deep Learning. In this study, Artificial immune system and machine learning algorithm was used for detecting and preventing malware activity. The system development utilized expert system methodology. The research work shows that adopting hybrid approaches for the development of malware detection applications provided significant advantages as 91.85% accuracy in maleware threat detection was achieved.

keywords:

Artificial Immune System, Machine Learning, Malware, Deep Learning

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References:

Ahmad, M. (2020). Malware in computer systems: Problems and solutions, IJID (International

Bace, R. and Mell, P. (2009). Special Publication on Intrusion Detection Systems. Infidel

Borisov, C.M. (2014). Pattern Recognition and Matching Learning,
August 2015,
Publisher: IEEE, John Wiley & Sons, New Jersey, USA. Vol. 4, pg. 31-33.

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