International Journal of Network Security & Its Applications (IJNSA) - ERA, WJCI Indexed
ISSN: 0974 - 9330 (Online); 0975 - 2307 (Print)
Webpage URL: https://airccse.org/journal/ijnsa.html
An ANN Approach for Network Intrusion Detection using Entropy based Feature Selection
AshalataPanigrahi and ManasRanjanPatra, Berhampur University, India
Abstract
With the increase in Internet users the number of malicious users are also growing day-by-day posing a serious problem in distinguishing between normal and abnormal behavior of users in the network. This has led to the research area of intrusion detection which essentially analyzes the network traffic and tries to determine normal and abnormal patterns of behavior.In this paper, we have analyzed the standard NSL-KDD intrusion dataset using some neural network based techniques for predicting possible intrusions. Four most effective classification methods, namely, Radial Basis Function Network, SelfOrganizing Map, Sequential Minimal Optimization, and Projective Adaptive Resonance Theory have been applied. In order to enhance the performance of the classifiers, three entropy based feature selection methods have been applied as preprocessing of data. Performances of different combinations of classifiers and attribute reduction methods have also been compared.
Keywords
Intrusion detection, Artificial Neural Network, attribute reduction
Original Source URL: https://airccse.org/journal/nsa/7315nsa02.pdf
Volume URL: https://airccse.org/journal/jnsa15_current.html
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