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无线传感器网络中虫洞攻击实时被动式探测
引用本文:鲁力,Muhammad Jawad HUSSAIN,朱金奇. 无线传感器网络中虫洞攻击实时被动式探测[J]. 软件学报, 2016, 27(12): 3085-3103
作者姓名:鲁力  Muhammad Jawad HUSSAIN  朱金奇
作者单位:电子科技大学 计算机科学与工程学院, 四川 成都 611731,电子科技大学 计算机科学与工程学院, 四川 成都 611731;电子科技大学 通信与信息工程学院, 四川 成都 611731,天津师范大学 计算机与信息工程学院, 天津 300387
基金项目:国家自然科学基金(61472068,61173171,61103227);中国博士后基金(2014M550466)
摘    要:在无线传感器网络所面临的安全问题中,虫洞攻击是最严重的威胁之一.由于无线传感器节点的资源非常有限,因此,适用于有线网络上的基于密码学的安全技术不能直接移植于无线传感网络.目前已知的传感网中,虫洞攻击的探测方案在应用上存在问题,这些方案或需要精确时间同步、或额外的定位算法或硬件、或有较大的通信开销,并且,现有方案均不能检测可自适应调整攻击策略的主动虫洞敌手.结合无线传感器网络的特点,提出了基于拓扑的被动式实时虫洞攻击探测方案,称为Pworm.通过利用虫洞攻击的主要特征——大量吸引网络流量和显著缩短平均网络路径,Pworm不需要任何额外的硬件,只需要收集网络中部分路由信息,就能实时地探测虫洞节点,即使是主动虫洞节点,也不能通过改变自身攻击策略而躲避探测.实验结果和分析表明:该方案具有轻量级、低漏报率、高可扩展性等优点,适用于大规模无线传感网络.

关 键 词:无线传感器网络  虫洞攻击  实时被动检测
收稿时间:2015-06-18
修稿时间:2015-07-27

Real-Time and Passive Wormhole Detection for Wireless Sensor Networks
LU Li,Muhammad Jawad HUSSAIN and ZHU Jin-Qi. Real-Time and Passive Wormhole Detection for Wireless Sensor Networks[J]. Journal of Software, 2016, 27(12): 3085-3103
Authors:LU Li  Muhammad Jawad HUSSAIN  ZHU Jin-Qi
Affiliation:School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China,School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China and School of Computer and Information Engineering, Tianjin Normal University, Tianjin 300387, China
Abstract:Wormhole attack is one of the severe threats to wireless sensor and ad hoc networks. Most of the existing countermeasures either demand high network overheads or require specialized hardware to capture the specific symptoms induced by the wormholes, which in result, limits their applicability. This paper exploits an inevitable symptoms of wormhole attack and proposes Pworm, a real-time and passive wormhole detection and localization scheme based on the key observation that a large amount of network traffic are attracted by the wormholes. The proposed scheme can silently observe the variations in network topology to infer the existence of wormholes. Besides the scheme solely depends on network routing information and does not demand any specialized hardware. System performance of the scheme is evaluated through extensive simulations of 100 to 500 nodes for various network scales and the results show that Pworm is well suited for false alarms with good scalability and low time delay.
Keywords:wireless sensor networks  wormhole attack  real-time and passive detection
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