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基于核聚类的无线传感器网络异常检测方案 被引量:17

An Anomaly Detection Scheme for Wireless Sensor Networks Based on Kernel Clustering
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摘要 针对无线传感器网络的自身特殊性和所面临的路由安全威胁,提出了一种基于核聚类的异常检测方案——KCAD,以检测路由攻击所导致的流量异常。该方案通过利用Mercer核,将输入空间的流量特征样本隐式地映射到高维特征空间,突出了不同样本间的特征差异,从而更好地完成聚类,提高了检测准确率,同时还针对流量特征样本做了时间维扩展,使之更能反映近期网络流量状况,减少了由于历史数据集影响所带来的误报。仿真实验结果表明,KCAD方案能够在较少的资源开销条件下,迅速、有效地检测出传感器网络中的攻击异常。 To the specific features of wireless sensor network and attack models met with routing protocols, a lightweight security scheme, KCAD (Kernel Clustering based Anomaly attack Detection), is proposed for detecting routing attacks. By using Mercer kernel function, the scheme can map the traffic feature sampies from their original space to a high dimensional feature space where the traffic feature samples are expected to be more separable, and then perform clustering in the high dimensional space. Meanwhile, in order to reduce the influence of historical data, we add time dimension to the traffic feature samples which can represent current network situation nicely. Simulation results show that KCAD has good veracity with less resource overhead.
出处 《传感技术学报》 CAS CSCD 北大核心 2008年第8期1442-1447,共6页 Chinese Journal of Sensors and Actuators
基金 国防基础科研项目资助(2720061361)
关键词 无线传感器网络 入侵检测 核聚类 路由攻击 wireless sensor network intrusion detection kernel clustering routing attack
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参考文献16

  • 1Akyildiz I F, Su W, Sankarasubramaniam Y, Cayirci E. Wireless Sensor Network: A Survey[J]. Computer Networks, 2002,38(4) : 393-422.
  • 2Estrin D, Govindan R, Heidemann J. Next Century Challenges: Scalable Coordination in Sensor Networks[C]//Proceedings of the Fifth Annual International Conference on Mobile Computing and Networks. Seattle: IEEE Computer Society, 1999, 263-270.
  • 3Perrig A, Stankovic J, Wagner D. Security in Wireless Sensor Networks[J]. Communications of the ACM, 2004, 47 (6): 53-57.
  • 4Kaufman L and Rousseeuw P. J. Finding Groups in Data: an Introduction to Cluster Analysis [M]. John Wiley & Sons, 1990.
  • 5Bezdek J C, Erhlich R, Full W. 1984. FCM:The Fuzzy C- Means Clustering Algorithm[J]. Comp. Geosci. 10:191-203.
  • 6Muller K, Mika S, Ratsch G, et al. An Introduction to Kernel-based Learning Algorithms [J]. IEEE Trans. on Neural Networks, 2001.
  • 7Scholkopf 13. The Kernel Trick for Distances[R]. Technical Report MSR TR-2000-51,19 May 2000.
  • 8Documit S, Grawal D P. Sell-Organized Criticality and Stochastic Learning Based Intrusion Detection System for Wireless Sensor Networks [C]// Proceedings of the IEEE Military Communications Conference (MILCOM 2003).
  • 9Rajasegarar S, Leckie C, Palaniswami M, Bezdek J C. Distributed Anomaly Detection in Wireless Sensor Networks [C]// Proceedings of the 10th IEEE Singapore International Conference on Communication System(ICCS 2006).
  • 10Loo C E, Ng M Y, Leckie C, Palaniswami M. Intrusion Detection for Routing Attacks in Sensor Networks[J]. International Journal of Distributed Sensor Networks, 2006, 2 (4): 313-332.

二级参考文献13

  • 1崔莉,鞠海玲,苗勇,李天璞,刘巍,赵泽.无线传感器网络研究进展[J].计算机研究与发展,2005,42(1):163-174. 被引量:730
  • 2Ian F,Akyildiz,Su Weilian.Yogesh Sankarasubramaniam,et al.Wireless Sensor Networks:A Survey[J].Computer Networks,2002,38(4):393-442.
  • 3Chris Karlof,David Wagner.Secure Routing in Wireless Sensor Networks:Attacks and Countermeasures[C]//First IEEE International Workshop on Sensor Network Protocols and Applications,2003,5.
  • 4Fei Hu,Neeraj K.Sharma.Security Considerations in Ad Hoc Sensor Networks[J].Ad Hoc Networks,2005,(3):69-89.
  • 5Adrian Perrig,John Stankovic,David Wanger.Security in Wireless Sensor Networks[J].Communications of the ACM,2004,47(6):53-57.
  • 6Yongguang Zhang,Wenke Lee.Intrusion Detection in Wireless Ad Hoc Networks[C]//Proc of The Sixth International Conference on Mobile Computing and Networking (MobiCom'2000),Boston,MA,2000:275-283.
  • 7Chien Chung Su,Ko Ming Chang,Yau Hwang Kuo.The New Intrusion Prevention and Detection Approaches for Clustering-based Sensor Networks[J].IEEE Communications So ciety/WCNC 2005:1927-1932.
  • 8Oleg Kachirski,Ratan Guha.Intrusion Detection Using Mobile Agents in Wireless Ad Hoc Networks[C]// IEEE Workshop on Knowledge Media Networking (KMN ' 02).Kyoto,JAPAN,2002:153-158.
  • 9Guy Helmer,Johnny s.k.Wong,Vasant Honavar,et al.Lightweight Agents for Intrusion Detection[J].Journal of Systems and Software,2003,(67):109-122.
  • 10Heinzelman W,Chandraksan A,Balakrishman.Energy-Efficient Communication Protocols for Wireless Microsensor Networks[C]//Proceeding of Hawaiian International Conference on Systems Science,2000.

共引文献38

同被引文献136

  • 1陈凤东,洪炳镕.基于动态阈值背景差分算法的目标检测方法[J].哈尔滨工业大学学报,2005,37(7):883-884. 被引量:43
  • 2李涛.基于免疫的网络安全风险检测[J].中国科学(E辑),2005,35(8):798-816. 被引量:40
  • 3俞波,杨珉,王治,高传善.选择传递攻击中的异常丢包检测[J].计算机学报,2006,29(9):1542-1552. 被引量:24
  • 4郑德华.ICP算法及其在建筑物扫描点云数据配准中的应用[J].测绘科学,2007,32(2):31-32. 被引量:60
  • 5Estrin D. Govindan R. Heidemann J. Next Century Challenges: Scalable Coordination in Sensor Networks[C]//Proceed ings of the Fifth Annual International Conference on Mobile Computing and Networks. Seattle: IEEE Computer Society, 1999, 263-270.
  • 6Strikos A. A Full Approach for Intrusion Detection in Wireless Sensor Networks[EB/OL] http; /www. it. kth. se/courses/ 2G1330. 2007.
  • 7Onat I, Miri A. An Intrusion Detection System for Wireless Sensor Networks[C]//Proceedings of the IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMOB 2005).
  • 8Rajasegarar S, I.eckie C, Palaniswami M, Bezdek J C. Distributed Anomaly Detection in Wireless Sensor Networks [C]//Proccedings of the 10th IEEE Singapore International Conference on Communication System(ICCS 2006).
  • 9Loo C E, Ng M Y. Lcckie C. Palaniswami M,et. al. Intrusion Detection for Routing Attacks in Sensor Networks[J]. International Journal of Distributed Sensor Networks, 2006, 2(4): 313-332.
  • 10Blazevic L, Capkun S. Self-Organization in Mo-Bile Ad Hoc Networks: the Approach of Terminodes [J]. IEEE Commun. Mag. , vol. 39, no. 6, 2001:161-174.

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