{"title":"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","authors":"Yu Nuo","doi":"10.1504/IJADS.2018.10007261","DOIUrl":null,"url":null,"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.","PeriodicalId":39414,"journal":{"name":"International Journal of Applied Decision Sciences","volume":"41 2 1","pages":"1-17"},"PeriodicalIF":0.0000,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A novel selection method of network intrusion optimal route detection based on naive Bayesian\",\"authors\":\"Yu Nuo\",\"doi\":\"10.1504/IJADS.2018.10007261\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":39414,\"journal\":{\"name\":\"International Journal of Applied Decision Sciences\",\"volume\":\"41 2 1\",\"pages\":\"1-17\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Applied Decision Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJADS.2018.10007261\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Economics, Econometrics and Finance\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Applied Decision Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJADS.2018.10007261","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
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.
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.