Journal of Cyber Security and Risk Auditing

Machine Learning for Cybersecurity Issues : A systematic Review

by 

Aseel Alshuaibi ;

Mohammed Almaayah ;

Aitizaz Ali

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Published: 2025/02/20

Abstract

With growing of the usage of the Information technologies and social networks, the identification of different network attacks, especially those not previously discovered, is an important concern that needs to be addressed. This paper is reviewing recent studies on security incidents and related security issues. The aim of the study is to clarify how Machine Learning techniques can influence cybersecurity. Moreover, this study aims to analyze and review previous studies related to machine learning (ML) and how could ML techniques improve the security. In addition, it will discuss and highlight different applications of ML in cybersecurity. As well as understand the use of ML in addressing some of cybersecurity problems. After reviewing previous studies and analyzing the results, the results show that machine learning are positively change the cybersecurity field. By mapping major machine learning algorithms with cyber-attacks and discuss the effectiveness of each algorithm for corresponding attack.

Keywords

Internet of Things (IoT)CybersecurityCyber-attacksIoT Assets and Threats

Doi Link

https://doi.org/10.63180/jcsra.thestap.2025.1.4

How to Cite the Article

Alshuaibi, A., Almaayah, M., & Ali, A. (2025). Machine Learning for Cybersecurity Issues : A systematic Review. Journal of Cyber Security and Risk Auditing, 2025(1), 36–46. https://doi.org/10.63180/jcsra.thestap.2025.1.4

Machine Learning for Cybersecurity Issues : A systematic Review is licensed under CC BY 4.0CCBY

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