WSN中一种基于扩展卡尔曼滤波器的虚假数据注入检测算法

为了有效地检测传感器网络中被注入的虚假数据，提出一种基于扩展卡尔曼滤波器（EKF）的虚假数据注入检测算法。首先通过监控邻近节点行为，使用EKF预测邻近节点未来状态；然后给出了使用不同的融合函数（平均、求和、最大、最小）时理论阈值的确定方法；最后为了克服本地检测机制的缺陷，将本地检测方法与系统监控模块有效配合，从而准确地区分出恶性事件和紧急事件。仿真实验结果表明，无论是在合成数据还是实时数据下进行测试，该算法都能为无线传感器网络进行安全的数据融合提供有效的入侵检测功能。...

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Bibliographic Details
Published in计算机应用研究 Vol. 31; no. 5; pp. 1475 - 1480
Main Author 熊伟
Format Journal Article
LanguageChinese
Published School of Computer，Chongqing College of Electronic Engineering，Chongqing 401331，Chin 2014
Subjects
扩展卡尔曼滤波器
数据融合
无线传感器网络
虚假数据
融合函数
阈值
wireless sensor networks
aggregation function
阈值
extended Kalman filter
虚假数据
threshold
无线传感器网络
数据融合
扩展卡尔曼滤波器
data aggregation
融合函数
false data
Online AccessGet full text
ISSN1001-3695
DOI10.3969/j.issn.1001-3695.2014.05.046

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Summary:为了有效地检测传感器网络中被注入的虚假数据，提出一种基于扩展卡尔曼滤波器（EKF）的虚假数据注入检测算法。首先通过监控邻近节点行为，使用EKF预测邻近节点未来状态；然后给出了使用不同的融合函数（平均、求和、最大、最小）时理论阈值的确定方法；最后为了克服本地检测机制的缺陷，将本地检测方法与系统监控模块有效配合，从而准确地区分出恶性事件和紧急事件。仿真实验结果表明，无论是在合成数据还是实时数据下进行测试，该算法都能为无线传感器网络进行安全的数据融合提供有效的入侵检测功能。
Bibliography:XIONG Wei （School of Computer, Chongqing College of Electronic Engineering, Chongqing 401331, China）
51-1196/TP
wireless sensor networks; data aggregation; false data; extended Kalman filter; aggregation function; threshold
In order to effectively detect the false injected data, this paper proposed a detection algorithm Of false injected data based on an extended Kalman filter. Firstly, by monitoring the behaviors of its neighbors , it used EKF to predict their future states. Secondly, using different aggregation functions （average, sum, max, and min）, it presented how to obtain a theoretical threshold. Finally, to overcome the limitations of local detection mechanisms, it illustrated how the proposed local detection approaches worked together with the system monitoring module to differentiate between malicious events and emergency events. Simulation results show that this proposed algorithm is suitable to provide intrusion detection capabilities for secure in-network aggregation in wireless sensor networks, whe
ISSN:1001-3695
DOI:10.3969/j.issn.1001-3695.2014.05.046