A New Data Mining Based Network Intrusion Detection Model

Abstract- As information systems are more widely used in the field of internet nowadays the need for secure networks is tremendously increased. New intelligent Intrusion Detection Systems (IDSs) based on sophisticated algorithms rather than current signature base detections are in demand. Due to emerging new attack methods there is often the need to update an installed Intrusion Detection System (IDS). Many of the current Intrusion Detection Systems are constructed by manual coding of expert knowledge, so changes to them are expensive and slow. In data mining based intrusion detection system we should have thorough knowledge about the particular domain in relation to intrusion detection so as to efficiently extract relative rule from huge amounts of records. This paper proposes a new ensemble boosted decision tree approach for intrusion detection system.