An Increment Feature Selection Approach for Intrusion Detection System in MANET
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 1
Abstract
Network security is very important in this internet world. Now, all kind of activities such as money transactions, buying and selling are done through internet only. Many security mechanisms have been introduced in the past decades in this direction. No one provides the sufficient detection accuracy on current internet attacks. Dynamics attacks are increasing daily due to the number of users increased in online. For providing better classification accuracy and detecting novel internet attacks, we propose an ideal intrusion detection system for improving the detection rate. The proposed system is the combination of Cuttle Fish Feature Selection algorithm, Extended Chi-square algorithm and the existing classification algorithm called IAEMSVM to build a better input sets to IDS. The experimental results of the proposed system show that the system is reduced the computation time with less features and better result when tested with KDD Cup 99 data set.
Authors and Affiliations
K. Rajesh Kambattan, R. Manimegalai, S. Ganapathy
Keywords
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