A Study on Fuzzy Rules for Intrusion Detection System

An intrusion detection system (IDS) is used to manage network traffic and monitors for suspicious activity and alerts the system or network administrator. One of the major properties of IDS is to respond for anomalous or malicious traffic by taking action such as blocking the user or source IP address from accessing the network. IDS can identify threats in various ways: 1) it detects specific signatures of known threats and protects against malware 2) it detects based on comparing traffic patterns against a baseline and looking for anomalies. 3) There are some IDS that simply generate an alert and 4) Some IDS perform an action or actions in response to a detected threat. In this paper, we have studied different fuzzy approaches for intrusion detection system specifically for anomaly detection system using Fuzzy set theory and we analyze Fuzzy rule and the fitness function of Genetic algorithm for anomaly based attack detection.