基于定性评估的WSN节点捕获攻击被动检测方法
A Passive Detection Approach of Capture Attacks in WSNs Based on Qualitative Evaluation

作者: 李晶博 , 张光卫 :北京邮电大学网络与交换技术国家重点实验室,北京;

关键词: 无线传感器网络捕获攻击被动入侵检测云模型Wireless Sensor Networks Capture Attacks Passive Intrusion Detection Cloud Model

摘要: 由于通常部署于外界,WSN节点易于被敌手捕获。传统捕获攻击的监测方法主要有基于缺席时间的监测及被动入侵检测两类,前者需要额外的通信开销,而后者则需要对网络整体信号强度进行统计分析,对单个节点入侵的识别通常不够敏感。本文利用云模型定性知识与定量数值之间的不确定性转换能力,对WSN节点之间通信中信号强度进行实时统计,建立信号强度云模型,得出节点是否遭遇入侵的定性判断,进而对可疑节点一段时间内信号强度进行分析,判断是否遭遇捕获攻击。仿真实验证明,该方法能够较大程度地提高检测的准确度,且误报率较低。

Abstract: Since the nodes of WSNs are always deployed on the outside, nodes are easy to be captured. The traditional detection approaches of capture attack can be categorized as approaches based on time of absence and approaches based on passive intrusion detection. The former requires extra communication cost, and the latter needs to carry on the statistical analysis of the whole network signal strength. In this paper, the qualitative and quantitative uncertainty conversion ability of cloud model is used to evaluate the signal strengths among WSN nodes real-time. Normal cloud models are built based on the evaluation. The qualitative judgments of nodes are made, and the capture attacks in WSNs can be detected in time. Simulation results show that, this method can greatly improve the detection accuracy, and that the false alarm rate is low.

文章引用: 李晶博 , 张光卫 (2014) 基于定性评估的WSN节点捕获攻击被动检测方法。 软件工程与应用, 3, 15-21. doi: 10.12677/SEA.2014.31003

参考文献

[1] Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., et al. (2002) Wireless sensor networks: A survey. Computer Networks, 38, 393-422.

[2] 孙利民, 李建中, 陈渝, 等 (2005) 无线传感器网络. 清华大学出版社, 北京.

[3] Perrig, A., Stankovic, J. and Wagner, D. (2004) Security in wireless sensor networks. Communications of the ACM, 47, 53-57.

[4] Ding, W., Laha, B., et al. (2010) First stage detection of compromised nodes in sensor networks. IEEE Sensors Applications Symposium (SAS), Limerick, 23-25 February 2010, 20-24.

[5] Ding, W., Yu, Y., et al. (2010) Distributed first stage detection for node capture. IEEE GLOBECOM Workshop (GC Wkshps), Miami, 6-10 December 2010, 1566-1570.

[6] Youssef, M., Mah, M. and Agrawala, A. (2007) Challenges: Device-free passive localization for wireless envi-ronments. Proceedings of the 13th Annual ACM International Conference on Mobile Computing and Networking, Montreal, 9-14 September 2007, 222-229.

[7] Moussa, M. and Youssef, M. (2009) Smart devices for smart Environments: Device-free passive detection in real environments. IEEE International Conference on Pervasive Computing and Communications (PerCom 2009), Galveston, 9-13 March 2009, 1-6.

[8] Kaltiokallio, O. and Bocca, M. (2011) Real-time intrusion detection and tracking in indoor environment through distributed RSSI processing. IEEE 17th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA), Toyama, 28-31 August 2011, 61-70.

[9] Mrazovac, B., Bjelica, M.Z. and Kukolj, D. (2012) System design for passive human detection using principal components of the signal strength space. IEEE 19th International Conference and Workshops on Engineering of Computer Based Systems (ECBS), Novi Sad, 11-13 April 2012, 164-172.

[10] Zhang, D., Ma, J., Chen, Q.B. and Ni, L.M. (2007) An RF-based system for tracking transceiver-free objects. 5th Annual IEEE International Conference on Pervasive Computing and Communications, White Plains, 19-23 March 2007, 135-144.

[11] Yang, J., Ge, Y., et al. (2010) Performing joint learning for passive intrusion detection in pervasive wireless environments. Proceedings of IEEE INFOCOM, San Diego, 14-19 March 2010, 1-9.

[12] Kosba, A.E., Saeed, A. and Youssef, M. (2012) RASID: A robust WLAN device-free passive motion detection system. IEEE International Conference on Pervasive Computing and Communications, Lugano, 19-23 March 2012, 180-189.

[13] Crossbrow Inc. (2003) MPR—Mote processor radio board user’s manual.

[14] 詹杰, 刘宏立, 刘述钢 (2011) 基于RSSI的动态权重定位算法研究. 电子学报, 1, 82-88.

[15] 李德毅, 杜鷁 (2005) 不确定性人工智能. 国防工业出版社, 北京.

[16] 吕辉军, 王晔, 李德毅, 等 (2003) 逆向云在定性评价中的应用. 计算机学报, 8, 1009-1014.

[17] 宋远骏, 李德毅, 杨孝宗, 等 (2000) 电子产品可靠性的云模型评价方法. 电子学报, 12, 68, 74-76.

分享
Top