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《Computer Engineering and Design》 2009-21
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Intrusion detection system based on support vector machines with simulated annealing algorithms

SHAN Jian-kui1,ZHAO Xue-feng1,2(1.School of Computer Engineering,Huaihai Institude of Technology,Lianyungang 222005,China;2.Graduate School of CAD/CAM,Sichuan University,Chengdu 610065,China)  
In order to improve the detection efficiency of IDS(intrusion detection system) under the small sample conditions,SVM(support vector machine) is employed to IDS.The parameters of SVM are the Key factors of detection efficiency and difficult to choose appropriate parameter values.Therefore,SA(simulated annealing) algorithms are used in the proposed SVM model to optimize the parameter selection and SVM with optimized parameters for intrusion detection is designed.Through applied to treat the sample data and comparison of detection ability between the above detection method and the IDS based on original SVM,the results show that the intrusion detection system based on SVM with SA is efficient,lower false rate,and shorten the training time and detection time.
【Fund】: 国家自然科学基金项目(40806011)
【CateGory Index】: TP393.08
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