Title: A novel selection method of network intrusion optimal route detection based on naive Bayesian
Authors: Yu Nuo
Addresses: Experimental Training Center, Xi'An University of Finance and Economic, Xi'An 710061, China
Abstract: In order to improve the network security performance and resist the increasingly complex and diversified network intrusion, and reduce the false alarm rate of network intrusion and improve the detection efficiency, this paper proposes the selection method of the network intrusion optimal route detection based on naive Bayesian. We selected the feature subset of network route data by the principal component analysis and accordingly processed the network route detection sample set, getting the input characteristics of network route detection. The research selected the new low dimensional feature of network route data through linear or nonlinear transformation, and used the naive Bayesian network structure to classify the new network route data set. Simulation results show that the proposed method can improve the detection rate of network intrusion optimal route and reduce the false alarm rate, getting a more perfect result of network intrusion detection.
Keywords: network intrusion detection; principal component analysis; PCA; normalisation; optimal route of network intrusion.
International Journal of Applied Decision Sciences, 2018 Vol.11 No.1, pp.1 - 17
Available online: 28 Nov 2017 *Full-text access for editors Access for subscribers Free access Comment on this article