一种基于朴素贝叶斯的网络入侵最优路由检测选择新方法

Q3 Economics, Econometrics and Finance
Yu Nuo
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引用次数: 2

摘要

为了提高网络安全性能,抵御日益复杂和多样化的网络入侵,降低网络入侵的虚警率,提高检测效率,本文提出了基于朴素贝叶斯的网络入侵最优路由检测的选择方法。通过主成分分析选择网络路由数据的特征子集,并对网络路由检测样本集进行相应的处理,得到网络路由检测的输入特征。该研究通过线性或非线性变换选择新的网络路由数据的低维特征,并使用朴素贝叶斯网络结构对新的网络路由数据集进行分类。仿真结果表明,该方法提高了网络入侵最优路由的检测率,降低了虚警率,得到了较为完善的网络入侵检测结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel selection method of network intrusion optimal route detection based on naive Bayesian
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.
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来源期刊
International Journal of Applied Decision Sciences
International Journal of Applied Decision Sciences Decision Sciences-Information Systems and Management
CiteScore
1.40
自引率
0.00%
发文量
61
期刊介绍: IJADS is a double-blind refereed international journal whose focus is to promote the infusion of the functional and behavioural areas of business with the concepts and methodologies of the decision sciences and information systems. IJADS distinguishes itself as a business journal with an explicit focus on modelling and applied decision-making. The thrust of IJADS is to provide practical guidance to decision makers and practicing managers by publishing papers that bridge the gap between theory and practice of decision sciences and information systems in business, industry, government and academia. Papers published in the journal must contain some link to practice through realistically detailed examples or real applications.
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