计算机应用与软件Issue(2)：310-313,4.DOI:10.3969/j.issn.1000-386x.2016.02.072
基于流量预测的 WSN 入侵检测技术
WSN INTRUSION DETECTION TECHNOLOGY BASED ON TRAFFIC PREDICTION
摘要
Abstract
In wireless sensor networks,in view of that the internal attacks impose serious threats on network security and normal operation, such as causing the network congestion and huge energy consumption and so on,we proposed a traffic prediction-based intrusion detection technology.First the technology uses autoregressive moving average model (ARMA)to build the ARMA (2,1)traffic forecasting model for nodes,then it uses the predicted traffic value to get the range of packet reception rate passing through the nodes,finally,it achieves the effect of detection by comparing whether the actual packet reception rate exceeds the forecasting range.Experimental results showed that under the same message playback rate condition,compared with single ARMA model,to use this technology had higher detection rate and lower false alarm rate,and meanwhile reduced the energy consumption of network nodes.关键词
无线传感器网络/内部攻击/入侵检测/自回归滑动模型/流量接收率Key words
Wireless sensor networks (WSN)/Internal attack/Intrusion detection/Autoregressive moving average model (ARMA)/Packet reception rate分类
信息技术与安全科学引用本文复制引用
彭军,余强,何明星..基于流量预测的 WSN 入侵检测技术[J].计算机应用与软件,2016,(2):310-313,4.基金项目
四川省国际合作项目（2009 HH0009）；国家科技部支撑计划项目（2011BAH26B00）；四川省信息安全创新团队建设项目（13TD0005）；面向物联网的入侵检测关键技术研究项目（szjj 2013－018）。 （）
