基于汇聚度的传感器网络Sinkhole攻击检测  

Sinkhole Attack Detection in Sensor Networks Based on Convergence Degree

作　　者：谢磊[1,2] 徐勇军[2] 祝跃飞[1] 潘勇[3] 

机构地区：[1]解放军信息工程大学信息工程学院,郑州450002 [2]中国科学院计算技术研究所,北京100080 [3]武汉理工大学计算机科学与技术学院,武汉430070

出　　处：《计算机工程》2009年第11期1-3,共3页Computer Engineering

基　　金：国家“863”计划基金资助项目(2006AA01Z223,2006AA01Z225);国家自然科学基金资助项目(60772070)

摘　　要：传感器网络以数据为中心的特殊流量汇聚模式尤其易受Sinkhole攻击。通过分析Sinkhole攻击点邻近区域的路由特点,提出一种新颖的基于汇聚度检测Sinkhole攻击的策略。该策略无需运行密码算法,无需额外通信开销,适用于不同网络部署密度、信道质量及攻击强度下的攻击检测。Sensor networks which are data-centric networks with special flow convergence pattern are highly vulnerable to the Sinkhole attack. On the analysis of routing feature in the neighboring region of Sinkhole attack point, a novel detection strategy of Sinkhole attack based on convergence degree is proposed. Without any cryptographic algorithms and additional communication cost, the strategy is suitable for various network deployment density, different channel condition and attack power.

关 键 词：传感器网络 Sinkhole攻击 汇聚度 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]