Rule Based Classifier Models For Intrusion Detection System

One key feature of intrusion detection systems is their ability to provide a view of unusual activity and issue alerts notifying administrators and/or block a suspected connection. Intrusion detection is a process of identifying and responding to malicious activity targeted at computing and networking resources. Over the past decade, the field of IDS has been driven into overdrive by the explosive proliferation of personal and server-based computers.There is need of a systematic and automated IDS development process rather than the pure knowledge based and engineering approaches which rely only on intuition and experience.This encourages studying some Data Mining based frameworks for Intrusion Detection. These frameworks use data mining algorithms to compute activity patterns from system audit data and extract predictive features from the patterns. Machine learning algorithms are then applied to the audit records that are processed according to the feature definitions to generate intrusion detection rules Keywordsintrusion detection,association rules,JRip,attacks