传感技术学报2018，Vol.31Issue(4)：595-601,7.DOI:10.3969/j.issn.1004-1699.2018.04.017
基于时间序列数据的无线传感器网络的异常检测方法
Anomaly Detection Method for Wireless Sensor Networks Based on Time Series Data
摘要
Abstract
With the development and widespread application of wireless sensor networks,focusing on the problems of high variation in sampling value from sensors and the increase of inaccuracy of event detection in wireless sensor networks,a method based on sensor network time series data is presented.Using the median of k normal data collected by the sensor to establish the pivot amount and construct the confidence interval,a method to calculate the data interval discrepancy is proposed to judge the origin of the anomaly. The experimental results show that the detection rate of the abnormal data in the sensor network is above 98% and the false alarm rate remains below 0.5%,which have some certain utilities and commonality.关键词
无线传感器网络/时间序列/置信区间/差异度/异常检测Key words
wireless sensor network/time series/confidence interval/difference degree/anomaly detection分类
信息技术与安全科学引用本文复制引用
彭能松,张维纬,张育钊,黄焯,郑力新..基于时间序列数据的无线传感器网络的异常检测方法[J].传感技术学报,2018,31(4):595-601,7.基金项目
华侨大学科研基金项目(13BS415) （13BS415）
华侨大学研究生科研创新能力培育计划项目(1611422007) （1611422007）
泉州市科技计划基金项目(2014Z112) （2014Z112）
福建省自然科学基金项目(2015J05125) （2015J05125）
国家自然科学基金项目(61372107) （61372107）
