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| 基于遗传算法优化SVM的嵌入式网络系统异常入侵检测 | |
| 引用本文： | 姜春茂,张国印,李志聪.基于遗传算法优化SVM的嵌入式网络系统异常入侵检测[J].计算机应用与软件,2011,28(2). |
| 作者姓名： | 姜春茂 张国印 李志聪 |
| 作者单位： | 1. 哈尔滨工程大学计算机学院,黑龙江,哈尔滨,150001;哈尔滨师范大学计算机科学技术与信息工程学院,黑龙江,哈尔滨,150001 2. 哈尔滨工程大学计算机学院,黑龙江,哈尔滨,150001 3. 哈尔滨师范大学计算机科学技术与信息工程学院,黑龙江,哈尔滨,150001 |
| 摘 要： | 由于传统嵌入式网络系统入侵检测方法难以获得较高的检测精度,提出基于遗传算法优化的支持向量机(GA-SVM)的网络入侵检测技术.支持向量机分类器能够较好地解决少样本、高维、非线性分类问题.然而,支持向量机训练参数的选择对其分类精度有着很大影响,遗传算法能够同时优化支持向量机的训练参数,采用遗传算法进行支持向量机的训练参数同步优化.实验结果表明,这种遗传算法优化的支持向量机分类入侵检测模型有着很高的检测精度. |
| 关 键 词： | 支持向量机 遗传算法 检测精度 入侵检测 |
ABNORMAL INTRUSION DETECTION FOR EMBEDDED NETWORK SYSTEM BASED ON GENETIC ALGORITHM OPTIMISED SVM |
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| Jiang Chunmao,Zhang Guoyin,Li Zhicong.ABNORMAL INTRUSION DETECTION FOR EMBEDDED NETWORK SYSTEM BASED ON GENETIC ALGORITHM OPTIMISED SVM[J].Computer Applications and Software,2011,28(2). | |
| Authors: | Jiang Chunmao Zhang Guoyin Li Zhicong |
| Affiliation: | Jiang Chunmao1,2 Zhang Guoyin1 Li Zhicong2 1(Institute of Computer,Harbin Engineering University,Harbin 150001,Heilongjiang,China) 2(College of Computer Science and Technology,Harbin Normal University,China) |
| Abstract: | As conventional intrusion detection method for embedded network system can't gain high detection accuracy,the network intrusion detection technology based on genetic algorithm optimised support vector machine(GA-SVM) is proposed in the paper.Support vector machine(SVM) classifier can well resolve non-linear classification problem with small training sample and high dimensions.However,the selection of training parameters of SVM has a great influence on classification accuracy.Genetic algorithm can consume le... |
| Keywords: | Support vector machine Genetic algorithm Detection accuracy Intrusion detection |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |