考虑时滞影响的无线传感网络蠕虫病毒自适应检测方法
Adaptive Detection of Worm Viruses in Wireless Sensor Networks Considering Time Delay
杨芳 1刘全明2
作者信息
- 1. 山西工程科技职业大学 计算机工程学院,山西 晋中 030619
- 2. 山西大学 计算机与信息技术学院,山西 太原 030006
- 折叠
摘要
无线传感网络中的蠕虫病毒攻击存在着一定的时滞情况,攻击检测难度较大.为了准确检测无线传感网络中的蠕虫病毒,提出一种考虑时滞影响的无线传感网络蠕虫病毒自适应检测方法.采集大量无线传感网络流量数据,对全部数据进行降维处理.在网络蠕虫病毒攻击存在时滞的情况下,将PGM-NMF算法和聚类分析方法相结合,实现无线传感网络节点的异常检测及分类,判断蠕虫攻击的类型,实现蠕虫病毒自适应检测.仿真结果表明:蠕虫病毒攻击时滞为 12 ms时,所提方法检测蠕虫病毒的漏报率为9.3%,成功率为95.50%,误报率为0.69%,漏检率为2.9%,蠕虫病毒自适应检测耗时平均值为5.0 s.
Abstract
The worm attacks in wireless sensor networks have certain time delays,and the detection of attacks is difficult.In order to accu-rately detect worms in wireless sensor networks,an adaptive detection method of worms in wireless sensor networks considering the effect of time delay is proposed.A large number of wireless sensor network traffic data are collected,and the dimension of all data is reduced.In the case of delay in network worm attack,PGM-NMF algorithm and clustering analysis method are combined to realize anomaly detec-tion and classification of wireless sensor network nodes,the type of worm attack is judged,and worm virus adaptive detection is realized.The simulation results show that when the delay of worm virus attack is 12 ms,the miss alarm rate of the proposed method is 9.3%,the success rate is 95.50%,the false alarm rate is 0.69%,the missed detection rate is 2.9%,and the average time of worm virus adaptive de-tection is 5.0 s.
关键词
无线传感网络/蠕虫病毒/时滞影响/聚类分析Key words
wireless sensor network/worm virus/time delay effect/cluster analysis引用本文复制引用
基金项目
山西省科学技术厅科技战略项目(202204031401130)
出版年
2024
国家科技期刊平台
NSTL
万方数据