Current Studies On Intrusion Detection System, Genetic Algorithm And Fuzzy Logic

Nowadays Intrusion Detection System (IDS) which is increasingly a key element of system security is usedto identifythe maliciousactivities in a computer system or network. There are differentapproachesbeingemployedin intrusion detectionsystems, butunluckilyeachof thetechniqueso far is notentirelyideal. Theprediction process mayproducefalse alarms in many anomaly based intrusion detection systems. Withtheconcept offuzzy logic, thefalse alarm rate in establishingintrusive activities can be reduced. Aset ofefficientfuzzy rules can be used to define the normal and abnormal behaviorsin a computer network.Therefore some strategy is needed for bestpromisingsecurity to monitor the anomalous behavior incomputer network. In this paper I present a few research papers regarding the foundations of intrusiondetection systems, the methodologies and good fuzzy classifiers using genetic algorithm which are the focusof current development efforts and the solution of the problem of Intrusion Detection System to offer a real-world view of intrusion detection.Ultimately, adiscussionof theupcomingtechnologies andvariousmethodologies which promise toimprovethecapabilityof computer systemsto detect intrusions isoffered.