{"title":"基于遗传支持向量机模型的优化算法","authors":"Lanying Li, Shaobin Ma, Yun Zhang","doi":"10.1109/ISCID.2014.99","DOIUrl":null,"url":null,"abstract":"Aiming at the problem of low accuracy in intrusion detection system, this paper established a genetic support vector machine (SVM) model according to the features of genetic algorithm and support vector machine algorithm. The model firstly optimizes the support vector parameters according to genetic algorithm, then we build the intrusion detection model with support vector machine optimized and use the model to detect. The experiments choose the proper parameters (c, s) through discussing the influence of support vector machines parameters to the detection accuracy. The results show that putting genetic support vector machine model into intrusion detection improved detection accuracy.","PeriodicalId":385391,"journal":{"name":"2014 Seventh International Symposium on Computational Intelligence and Design","volume":"72 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Optimization Algorithm Based on Genetic Support Vector Machine Model\",\"authors\":\"Lanying Li, Shaobin Ma, Yun Zhang\",\"doi\":\"10.1109/ISCID.2014.99\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the problem of low accuracy in intrusion detection system, this paper established a genetic support vector machine (SVM) model according to the features of genetic algorithm and support vector machine algorithm. The model firstly optimizes the support vector parameters according to genetic algorithm, then we build the intrusion detection model with support vector machine optimized and use the model to detect. The experiments choose the proper parameters (c, s) through discussing the influence of support vector machines parameters to the detection accuracy. The results show that putting genetic support vector machine model into intrusion detection improved detection accuracy.\",\"PeriodicalId\":385391,\"journal\":{\"name\":\"2014 Seventh International Symposium on Computational Intelligence and Design\",\"volume\":\"72 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Seventh International Symposium on Computational Intelligence and Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCID.2014.99\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Seventh International Symposium on Computational Intelligence and Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCID.2014.99","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimization Algorithm Based on Genetic Support Vector Machine Model
Aiming at the problem of low accuracy in intrusion detection system, this paper established a genetic support vector machine (SVM) model according to the features of genetic algorithm and support vector machine algorithm. The model firstly optimizes the support vector parameters according to genetic algorithm, then we build the intrusion detection model with support vector machine optimized and use the model to detect. The experiments choose the proper parameters (c, s) through discussing the influence of support vector machines parameters to the detection accuracy. The results show that putting genetic support vector machine model into intrusion detection improved detection accuracy.