Data Mining based Hybrid Intrusion Detection System

Provided by: Creative Commons
Topic: Data Management
Format: PDF
Mankind has become more technology dependent and expects World Wide Web to handle daily requirements like newspapers, marketing, online transactions etc. An intrusion detection system is proposed using Decision Table/Naive 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.

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