摘要
入侵检测是网络安全的重要领域。安全问题的日益严峻对于检测方法提出更高的要求。支持向量机是一种基于小样本学习的有效工具。继它在字体识别,人脸识别中得到成功应用后,它被成功地应用到入侵检测领域中。介绍了支持向量机的多种算法,例如二分类的支持向量机,一分类的支持向量机,多分类的支持向量机和针对大量训练样本的支持向量机在入侵检测中的应用。通过比较发现,用支持向量机进行检测入侵大大提高了入侵检测系统的性能。
Intrusion detection is one of the important fields in network security. The serious security problems require better performance for intrusion detection system. Support vector machine （SVM） is an effective learning tool for small size samples. After its successive application in letter recognition, face recognition and so on, it found its application in intrusion detection. The applications of many algorithms of SVM, such as two_class SVM, one to two class SVM, multi_class SVM and the algorithm solving training on large training samples in intrusion detection are introduced. Detecting intrusion using SVM improves the detection performance.
出处
《计算机工程与设计》
CSCD
北大核心
2007年第10期2297-2299,共3页
Computer Engineering and Design
基金
十.五军事通讯预研基金项目(4100104030)
关键词
网络安全
入侵检测
支持向量机
network security
intrusion detection
support vector machine
