Survey: Learning Techniques for Intrusion Detection System (IDS)
The neural network approaches used for intrusion detection in the recent research papers has been surveyed and an extreme learning approach to solve the training time issue is proposed.
Abstract
A B S T R A C T An intrusion detection system (IDS) is a software application that monitors network or system activities for malicious activities. The research on neural network methods and machine learning techniques to improve the network security by examining the behavior of the network as well as that of threats is done in the rapid force. There are several techniques for intrusion detection which exist at present to provide more security to the network, however many of those are static. Many researchers used machine-learning techniques for intrusion detection, but some shows poor detection, some techniques takes large amount of training time. In this paper, learning approaches i.e. neural network approaches used for intrusion detection in the recent research papers has been surveyed and proposed an extreme learning approach to solve the training time issue.