Author : A Shriya 1
Date of Publication :7th August 2016
Abstract: In the current age Intrusion detection is an interest in and challenging area. As there are now a few exploration works are as of now done and the outcome change is in advancement. In this dissertation a hybrid approach has been proposed which is based on association rule mining and Intrusion Detection Using Swarm Intelligence Based on Iterative Selection. The NSL-KDD dataset is used. First normal and attack nodes are separated. Then normal node is checked for suspicious behavior. Then association rule mining is applied to form the associated for the next preprocessing. Then we check the threshold value obtained for the different intrusion types. If it is passed the threshold velocity assigned, then it will be categorized as the specific attack. We have considered a Denial of Service (DoS), User to Root (U2R), Remote to User (R2L) and Probing (Probe) attacks in this research work. The results show the improvement in detection as compared to the previous method.
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