| 一种基于特征选择的入侵检测方法 |
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| 引用本文： | 崔亚芬,解男男.一种基于特征选择的入侵检测方法[J].吉林大学学报(理学版),2015,53(1):112-116. |
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| 作者姓名： | 崔亚芬 解男男 |
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| 作者单位： | 1. 吉林省招生委员会办公室, 长春 130033； 2. 吉林大学 计算机科学与技术学院, 长春 130012 |
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| 基金项目： | 国家自然科学基金，吉林省重大科技专项基金 |
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| 摘 要： | 针对入侵检测中网络数据高维度、 大规模所带来的问题, 基于特征选择方法Fisher在网络安全数据集中的应用, 提出一种基于特征选择的通用入侵检测框架. 该方法通过提取关键特征, 降低安全数据的维度； 采用K近邻方法作为分类器, 验证特征选择后的检测效果. 实验结果表明, 该方法能在较少特征的情况下达到较高的检测率, 具有较好的可行性.
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| 关 键 词： | 入侵检测 Fisher特征选择 K近邻算法 |
| 收稿时间： | 2014-11-17 |
An Intrusion Detection Method Based on Feature Selection |
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| CUI Yafen,XIE Nannan.An Intrusion Detection Method Based on Feature Selection[J].Journal of Jilin University: Sci Ed,2015,53(1):112-116. |
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| Authors: | CUI Yafen XIE Nannan |
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| Institution: | 1. Jilin Admission and Examinations Committee Office, Changchun 130033, China;2. College of Computer Science and Technology, Jilin University, Changchun 130012, China |
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| Abstract: | This paper concerns about the problems about processing large\|scale and high dimension network datasets in intrusion detection. The typical feature selection algorithm Fisher was used in network security datasets, in order to reduce the dimension of features. K nearest neighbor algorithm was
used as the classify algorithm, to evaluate the detection rate. A general intrusion detection framework based on feature selection was presented and realized. Experiments show it has a satisfying detection accuracy with less features and a good feasibility. |
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| Keywords: | intrusion detection Fisher feature selection K-nearest neighbor algorithm |
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