In the proposed hybrid intrusion detection process, misuse detection and anomaly detection model is integrated to detect the attack in traffic pattern. In misuse detection model, the traffic pattern is classified into known attack and not known attack. Each extracted normal data set does not have known attack and it contains small amount of varied connection patterns than overall normal data set. Anomaly detection model classifies the not known attack as normal data set and unknown attack thus improving the performance of normal traffic behavior. Experiment is carried out using NSL –KDD dataset and performance of proposed approach is compared with traditional learning approaches in terms of training time, testing time, false positive ratio and detection ratio. The proposed method detects the known attacks and unknown attacks with ratio of 99.8 % and 52% respectively.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.