摘要
网络的安全性问题一直是大家所关心的热门话题,网络病毒和网络攻击的防护措施也不断革新。以动态跟踪网络数据并实时监控来进行网络安全管理为基础,阐述了支持向量机SVM算法的统计学习理论及分类原理,设计出了网络攻击检测模型,并对该模型进行性能分析。通过KDDCUP99数据集以及捕获的数据仿真得出,该模型对网络攻击检测具有较高的准确性和泛化能力。
The problem of network security has been a hot topic to us,and the protection for the virus and attack of network is innovation.Based on the dynamic tracking and real-time monitoring to network data,research on the statistical learning theory and classification theory of svm,and designed a network attack detection model and analysis the performance of the model.Simulation with KDDCUP99 data set and obtained that the model of network attack detection has high accuracy and generalization ability.
出处
《长江大学学报（自然科学版）》
CAS
2011年第8期81-84,279,共4页
Journal of Yangtze University(Natural Science Edition)
基金
国家自然科学基金项目(61072138)
