2003 | OriginalPaper | Chapter
Comparison of BPL and RBF Network in Intrusion Detection System
Authors : Chunlin Zhang, Ju Jiang, Mohamed Kamel
Published in: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing
Publisher: Springer Berlin Heidelberg
Included in: Professional Book Archive
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In this paper, we present the performance comparison results of the backpropagation learning (BPL) algorithm in a multilayer perceptron (MLP) neural network and the radial basis functions (RBF) network for intrusion detection. The results show that RBF network improves the performance of intrusion detection systems (IDSs) in anomaly detection with a high detection rate and a low false positive rate. RBF network requires less training time and can be optimized to balance the detection and the false positive rates.