Soft Computing-Based Intrusion Detection Approaches: An Analytical Study

Abstract

In the recent days, intrusion detection system using soft computing methods is one of the most interesting and attractive areas of research. Soft computing majorly undergoes with uncertainty, partial truth to gain robustness and low-cost solution. Intrusion detection system is a device or software application that monitors a network or system from unwanted activities. If the system detects any malware, it reports to the administrator or collects using security information. To develop efficient security methods, many researchers used fuzzy logic, neural network, machine learning, support vector machines, evolutionary computation, and probabilistic reasoning techniques. In this paper, a brief analysis has been conducted on various soft computing techniques for the successful detection of intrusive behaviors. Further, some future challenges with advantages and limitations are highlighted in a successive manner.