Indian Journal of Science and Technology

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Data Mining Based Hybrid Intrusion Detection System


Affiliations
1 Dept. of Information Technology, Birla Institute of Technology, Mesra, Ranchi, Jhrakhand, India
 

An intrusion detection system is proposed using Decision Table/Naïve Bayes (DTNB). The Proposed system uses a hybrid classifier DTNB that is used to identify possible intrusions. The system is trained using a subset of the NSL KDD Cup dataset. The trained model is then tested using a subset of NSL KDD Cup dataset. The DTNB hybrid classifier is able to detect intrusion with a superior detection rate.

Keywords

Anomaly Detection, DTNB, IDS, Misuse Detection
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  • Data Mining Based Hybrid Intrusion Detection System

Abstract Views: 263  |  PDF Views: 0

Authors

Chandrashekar Azad
Dept. of Information Technology, Birla Institute of Technology, Mesra, Ranchi, Jhrakhand, India
Vijay Kumar Jha
Dept. of Information Technology, Birla Institute of Technology, Mesra, Ranchi, Jhrakhand, India

Abstract


An intrusion detection system is proposed using Decision Table/Naïve Bayes (DTNB). The Proposed system uses a hybrid classifier DTNB that is used to identify possible intrusions. The system is trained using a subset of the NSL KDD Cup dataset. The trained model is then tested using a subset of NSL KDD Cup dataset. The DTNB hybrid classifier is able to detect intrusion with a superior detection rate.

Keywords


Anomaly Detection, DTNB, IDS, Misuse Detection



DOI: https://doi.org/10.17485/ijst%2F2014%2Fv7i6%2F54329