"Intrusion Detection System Using Fuzzy Clustring Algorithm"

"Nowadays Intrusion Detection System (IDS) which is increasingly a key elementof system security is used to identify the malicious activities in a computer system and-network. There are different approaches being employed in intrusion detection systems,but unluckily each of the technique so far is not entirely ideal. The prediction processmay produce false alarms in many anomaly based intrusion detection systems. To achievethat, this paper proposes IDS model based on Fuzzy Logic. Proposed model consists ofthree parts Client side model which include simple bank application, IDS model in whichpreviously defined testing set and training set are defined with Fuzzy algorithm andApriori algorithm and Admin model which are define some rule for user and show systemresult. Also IDS model contain Artificial Neural Network which is useful for self-intrusiondetection system. This manually update database we discover self-detection and updat-ing technique by using artificial neural network algorithm. Intrusion Detection System,can detect, prevent and react to the attacks. In our system when client attacks on serversystem our system detects that attack and blocks that client and that pattern of attackis stored at admin side. If another client attacks with same pattern then that client isdetected and blocked. Admin performs Turing test for client by generating questions."