摘要
提出了一种基于稀松模糊定位算法的网络入侵特征检测算法。新算法通过采集初始网络入侵特征,组建特征集合。利用稀松运动特征匹配算法最大程度上纠正由于特征模糊带来的弊端。保证跟踪匹配过程中,运用较少的入侵特征点完成后期的多个匹配,大幅降低匹配时间,消除匹配误差问题,通过将全局搜索和局部搜索机制有机地结合,保证检测的准确性。实验结果表明,利用本文算法进行入侵检测,能够有效提高检测的准确性。
This paper proposes a fuzzy positioning algorithm based on poor network intrusion feature detection algorithm. The new algorithm through the acquisition of initial network intrusion characteristics, a feature set. Using poor motion feature matching algorithm on the maximum correct due to the disadvantages of the fuzzy characteristics bring. Ensuring the tracking matching process, the use of less invasion of feature point matching complete later more and greatly reduce matching time, eliminate matching error problem, the global search and local search mechanism of organic combine, guarantee the accuracy of the test. The experimental results show that this algorithm using intrusion detection, and it can effectively improve the accuracy of detection.
出处
《科技通报》
北大核心
2014年第2期233-235,共3页
Bulletin of Science and Technology
基金
教育部高职高专电子信息类教学指导委员会项目(GZ31)
关键词
网络攻击
节点定位
约束模型
network attack
node localization
constraint model
