Rachmawati, Anggi and Yossaepurrohman, Yossaepurrohman (2022) Analysis of Machine Learning Systems for Cyber Physical Systems. International Transactions on Education Technology (ITEE), 1 (1). pp. 1-9. ISSN 2963-1947

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Abstract

This study summarizes major literature reviews on machine learning systems for network analysis and intrusion detection. Furthermore, it provides a brief lesson description of each machine learning approach. Because data is so important in machine learning methods, this study The primary tools for assessing network traffic and spotting anomalies are machine learning approaches, and the study focuses on the datasets utilized in these techniques. This research examine the multiple advantages (reasonable use) that machine learning has made possible, particularly for security and cyber-physical systems, including enhanced intrusion detection techniques and judgment accuracy. Additionally, this study discusses the difficulties of utilizing machine learning for cybersecurity and offers suggestions for further study.

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