{"title":"基于高速精确遗传算法神经网络的网络入侵检测方法","authors":"Jingwen Tian, Meijuan Gao","doi":"10.1109/NSWCTC.2009.228","DOIUrl":null,"url":null,"abstract":"Aimed at the network intrusion behaviors are characterized with uncertainty, complexity, diversity and dynamic tendency and the advantages of neural network, an intrusion detection method based on high speed and precise genetic algorithm neural network is presented in this paper. The high speed and precise genetic algorithm neural network is combined the adaptive and floating-point code genetic algorithm with BP network which has higher accuracy and faster convergence speed. We construct the network structure, and give the algorithm flow. We discussed and analyzed the impact factor of intrusion behaviors. With the ability of strong self-learning and faster convergence of high speed and precise genetic algorithm neural network, the network intrusion detection method can detect various intrusion behaviors rapidly and effectively by learning the typical intrusion characteristic information. The experimental result shows that this intrusion detection method is feasible and effective.","PeriodicalId":433291,"journal":{"name":"2009 International Conference on Networks Security, Wireless Communications and Trusted Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Network Intrusion Detection Method Based on High Speed and Precise Genetic Algorithm Neural Network\",\"authors\":\"Jingwen Tian, Meijuan Gao\",\"doi\":\"10.1109/NSWCTC.2009.228\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aimed at the network intrusion behaviors are characterized with uncertainty, complexity, diversity and dynamic tendency and the advantages of neural network, an intrusion detection method based on high speed and precise genetic algorithm neural network is presented in this paper. The high speed and precise genetic algorithm neural network is combined the adaptive and floating-point code genetic algorithm with BP network which has higher accuracy and faster convergence speed. We construct the network structure, and give the algorithm flow. We discussed and analyzed the impact factor of intrusion behaviors. With the ability of strong self-learning and faster convergence of high speed and precise genetic algorithm neural network, the network intrusion detection method can detect various intrusion behaviors rapidly and effectively by learning the typical intrusion characteristic information. The experimental result shows that this intrusion detection method is feasible and effective.\",\"PeriodicalId\":433291,\"journal\":{\"name\":\"2009 International Conference on Networks Security, Wireless Communications and Trusted Computing\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-04-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Networks Security, Wireless Communications and Trusted Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NSWCTC.2009.228\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Networks Security, Wireless Communications and Trusted Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NSWCTC.2009.228","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Network Intrusion Detection Method Based on High Speed and Precise Genetic Algorithm Neural Network
Aimed at the network intrusion behaviors are characterized with uncertainty, complexity, diversity and dynamic tendency and the advantages of neural network, an intrusion detection method based on high speed and precise genetic algorithm neural network is presented in this paper. The high speed and precise genetic algorithm neural network is combined the adaptive and floating-point code genetic algorithm with BP network which has higher accuracy and faster convergence speed. We construct the network structure, and give the algorithm flow. We discussed and analyzed the impact factor of intrusion behaviors. With the ability of strong self-learning and faster convergence of high speed and precise genetic algorithm neural network, the network intrusion detection method can detect various intrusion behaviors rapidly and effectively by learning the typical intrusion characteristic information. The experimental result shows that this intrusion detection method is feasible and effective.