Intrusion Detection using Machine Learning Techniques: An exhaustive review
Ashwathy Anda Chacko, M. Roshni Thanka, Bijolin Edwin, Shamila Ebenezer A · 2023
With the enormous growth of computers and data networks, as well as the vast number of relevant applications, cyber security has recently received a great deal of attention. The Internet has become more vulnerable to planned and extended cybercrimes. Consequently, the development of a powerful intrusion detection system to eliminate various cyberattacks in a network has become critical. Even though traditional security measures exist to detect and prevent cyberattacks, these measures are ineffective because cybercriminals are intelligent enough to circumvent all of them. Many cybersecurity applications employ machine learning (ML) techniques. This paper reviews the literature on intrusion detection using machine-learning techniques. This paper gives a brief overview of various machine learning methods and security datasets that are commonly used. Additionally, various metrics for evaluating the classification model's performance are discussed. This review paper looks at different machine learning methods for intrusion detection and the challenges that we can face during the application of machine learning.