南京师大学报（自然科学版）Issue(1)：87-92,6.
基于小波分析的无线传感网实时异常检测算法
Wavelet Analysis-Based Real-Time Anomaly Detection Algorithm for Wireless Sensor Network
摘要
Abstract
Anomaly detection can detect new and unknown attacks,which has great significance on the wireless sensor networks security. Nowadays,the proposed anomaly detection schemes has poor real-time,high false positive rate and the large amount of computational overhead, and hence the schemes are not suitable for wireless sensor networks. In this paper,a wavelet analysis-based real-time anomaly detection ( Wavelet Analysis-based Real-time Anomaly Detection, WARAD) algorithm for wireless sensor network is proposed. Throughout the detecting process, the WARAD algorithm reversely collects the real-time network traffic,and then uses the variance of the wavelet coefficients in the small-scale interval to compute the Hurst values,which can improve the real-time and the accuracy of anomaly detection,and reduce the computational complexity of solving the Hurst values. Finally,the WARAD algorithm-based intrusion detection system is implemented on the platform of MeshIDE. The experimental results showed that the proposed algorithm greatly improved the real-time of anomaly detection for wireless sensor networks,and reduced the false positive rate and the false negative rate of anomaly detection.关键词
无线传感器网络/安全/异常检测/小波分析/Hurst参数Key words
wireless sensor networks/security/anomaly detection/wavelet analysis/Hurst parameter分类
信息技术与安全科学引用本文复制引用
李致远,朱求志,吴永焜,唐振宇,胡华明..基于小波分析的无线传感网实时异常检测算法[J].南京师大学报（自然科学版）,2014,(1):87-92,6.基金项目
国家自然科学基金(61202474、61103195)、江苏省自然科学基金( BK20130528)、江苏大学高级专业人才科研启动基金项目(12JDG049)、江苏大学本科生创新计划项目(2012075) （61202474、61103195）
