Review on Intrusion Detection System (IDS) for Network Security using Machine Learning Algorithms

Abstract

With the advancement in the artificial intelligence technologies and development of fifth-generation networks, a network may face many hazards and challenges as the number of users are accessing the network simultaneously which makes the user to think of losing the confidentiality of the data and hence the network to be considered for security. Threats on the network can be classified in many ways and to detect such threats an Intrusion detection system (IDS) is the one which is mainly used. A network can be attacked in two ways as minor attack and major attack. Denial-of-Service (DoS) and Prob attacks belong to major kind and User-to-Root (U2R) and Remote-to-Login (R2L) goes to minor attack categories. The minor attacks are also called as rare attacks which are very injurious for a host and it is very difficult to recognize these attacks. This paper consists of a survey made on IDS and different algorithms used to implement these IDSs using machine learning.