Machine Learning in Cybersecurity
Deepa Fernandes Prabhu, L. Sudha, Pandi Kumari M. R., A. Adaikkammai, P. Aparna, Siva Subramanian R, V. Sathya · 2025
This survey paper explores how machine learning (ML) has been useful in handling modern security issues. In today's dynamic world of cybersecurity threats, conventional means of protection are not sufficient to counter modern day threats. This field introduces new approaches to improve threat identification and mitigation measures. The paper is introduced with an analysis of modern threats in the sphere of cybersecurity and the use of machine learning. Basic concepts of ML and how they can be used in cybersecurity are described to build the necessary background for the next topics. The paper explores topics such as detecting and mitigating advanced attacks using adversarial machine learning and machine learning in cryptography and blockchain. The methods for protecting the privacy of data in ML are discussed to meet the requirements of data protection laws. With this in mind, this systematic review shall provide key insights to enable researchers and practitioners in the development of effective and robust machine learning based cybersecurity solutions.