灰洞检测：基于链路质量估计的看门狗算法

doi:10.3969/j.issn.1006-2475.2014.02.042

摘要/Abstract

摘要： 传感器网络中的数据传输依靠节点间的合作，但是节点被入侵者俘获而成为恶意节点后会发起灰洞攻击，从而大幅降低网络性能。现有的检测算法主要依靠统计节点的接收转发行为来检测灰洞。但是传感器网络的链路质量会导致节点的自然丢包，现有检测算法难以有效区分。针对此问题本文提出基于链路质量估计的看门狗算法以及最优阈值理论，利用链路质量来修正节点的统计结果，根据网络环境调整参数，最小化误报、漏报概率，提高算法正确率。仿真实验结果表明本文提出的算法能够有效地降低检测误报、漏报率。

关键词: 灰洞检测, 链路质量, 看门狗算法

Abstract: Data transmission among wireless sensor network relies on cooperation between nodes, but nodes are easily captured by malicious intruder and then captured nodes launch gray-hole attacks, which thereby significantly reduce network performance. Existing detection algorithms mainly rely on statistical receiving and forwarding behavior to detect gray holes. But these algorithms can’t effectively distinguish natural loss due to unstable link quality of sensor network and the gray hole. To solve this problem, a watchdog algorithm based on link quality is proposed. To improve performance, this algorithm uses link quality to revise statistical observation and adjust the threshold according to the network environment. Simulation results show that the proposed algorithm can effectively reduce the false positive and false negative rate.

Key words: gray hole detection, link quality, watchdog algorithm

中图分类号:

TP393.08

蒋锟，汪芸. 灰洞检测：基于链路质量估计的看门狗算法[J]. 计算机与现代化, doi: 10.3969/j.issn.1006-2475.2014.02.042.

JIANG Kun, WANG Yun.

Gray Hole Detection: Watchdog Algorithm Based on Link Quality Estimation

[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2014.02.042.

参考文献 16

[1]	De Couto D S J, Aguayo D, Bicket J, et al. A high-throughput path metric for multi-hop wireless routing[J]. Wireless Networks, 2005,11(4):419-434.
[2]	Sang L, Arora A, Zhang H. On exploiting asymmetric wireless links via one-way estimation[C]// Proceedings of the 8th ACM International Symposium on Mobile Ad Hoc Networking and Computing. 2007:11-21.
[3]	Jakllari G, Eidenbenz S, Hengartner N, et al. Link positions matter: A noncommutative routing metric for wireless mesh networks[J]. IEEE Transactions on Mobile Computing, 2012,11(1):61-72.
[4]	Lin S, Zhou G, Whitehouse K, et al. Towards stable network performance in wireless sensor networks[C]//Proceedings of the 30th IEEE Real-Time Systems Symposium. 2009:227-237.
[5]	Zhang H, Sang L, Arora A. Comparison of data-driven link estimation methods in low-power wireless networks[J]. IEEE Transactions on Mobile Computing, 2010,9(11):1634-1648.
[6]	Draves R, Padhye J, Zill B. Comparison of routing metrics for static multi-hop wireless networks[J]. ACM SIGCOMM Computer Communication Review, 2004,34(4):133-144.
[7]	Gnawali O, Yarvis M, Heidemann J, et al. Interaction of retransmission, blacklisting, and routing metrics for reliability in sensor network routing[C]// Proceedings of the 1st IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks. 2004:34-43.
[8]	Cerpa A, Wong J L, Potkonjak M, et al. Temporal properties of low power wireless links: Modeling and implications on multi-hop routing[C]// Proceedings of the 6th ACM International Symposium on Mobile Ad Hoc Networking and Computing. 2005:414-425.
[9]	Gu Y, He T. Data forwarding in extremely low duty-cycle sensor networks with unreliable communication links[C]// Proceedings of the 5th International Conference on Embedded Networked Sensor Systems. 2007:321-334.
[10]	Fonseca R, Gnawali O, Jamieson K, et al. Four-bit wireless link estimation[C]// Proceedings of the 6th Workshop on Hot Topics in Networks. 2007.
[11]	Marti S, Giuli T J, Lai K, et al. Mitigating routing misbehavior in mobile ad hoc networks[C]// Proceedings of the 6th Annual International Conference on Mobile Computing and Networking. 2000:255-265.
[12]	Patcha A, Mishra A. Collaborative security architecture for black hole attack prevention in mobile ad hoc networks[C]// Proceedings of the 2003 IEEE Radio and Wireless Conference. 2003:75-78.
[13]	Nasser N, Chen Y. Enhanced intrusion detection system for discovering malicious nodes in mobile ad hoc networks[C]// Proceedings of the 2007 IEEE International Conference on Communications. 2007:1154-1159.
[14]	Li X, Lu R, Liang X, et al. Side channel monitoring: Packet drop attack detection in wireless ad hoc networks[C]// Proceedings of the 2011 IEEE International Conference on Communications. 2011.
[15]	Hayajneh T, Krishnamurthy P, Tipper D, et al. Detecting malicious packet dropping in the presence of collisions and channel errors in wireless ad hoc networks[C]// Proceedings of the 2009 IEEE International Conference on Communications. 2009:1062-1067.
[16]	Shila D M, Cheng Y, Anjali T. Channel-aware detection of gray hole attacks in wireless mesh networks[C]//Proceedings of the 28th IEEE Conference on Global Telecommunications. 2009:3998-4003.