Abstract
As a hot issue, wireless sensor network have gained widely attention. WSNs in general and in nature are unattended and physically reachable from the outside world, they could be vulnerable to physical attacks in the form of node capture or node destruction. These forms of attacks are hard to protect against and require intelligent prevention methods. It is necessary for WSNs to have security measures in place as to prevent an intruder from inserting compromised nodes in order to decimate or disturb the network performance. In this paper we present an intrusion detection algorithm for wireless sensor networks which does not require prior knowledge of network behavior or a learning period in order to establish this knowledge. We have taken a more practical approach and constructed this algorithm with small to middle-size networks in mind, like home or office networks. The proposed algorithm is also dynamic in nature as to cope with new and unknown attack types. This algorithm is intended to protect the network and ensure reliable and accurate aggregated sensor readings. Theoretical simulation results in three different scenarios indicate that compromised nodes can be detected with high accuracy and low false alarm probability.
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References
Maronna, R.A., Martin, R.D., Yohai, V.J.: Robust Statistics: Theory and Methods, vol. ch. 6.9.1, pp. 205–208. Wiley Publisher, Chichester (2006)
Hussain, S., Mohamed, M.A., Holder, R., Almasri, A., Shukur, G.: Performance evaluation based on the robust mahluationbis distance and multilevel modelling using two new strategies (February 2008)
Filzmoser, P.: A multiivariate outlier detection method
Alberts, P., Kuhn, M.: Security in ad hoc networks: A general intrusion detection architecture enhancing trust based approaches. In: First International Workshop on Wireless Information Systems, 4th International Conference on Enterprise Information Systems (2002)
Liu, F., Cheng, X., Chen, D.: Insider Attacker Detection in Wirelss Sensor Networks. In: IEEE Proceedings INFOCOM 2007 (2007)
Alqallaf, F.A., Konis, K.P., Douglas Martin, R., Zamar, R.H.: Scalable robust covariance and correlation estimates for data mining. In: ACM SIGKDD 2002, Edmonton, Alberta, Canada, pp. 14–23 (2002)
Ngai E.C.H.: Intrusion Detection for Wireless Sensor Networks. Ph.D. – Term 2 Paper (2005)
Sarma, H.K.D., Manipal, S., Kar, A.: Security Threats in Wireless Sensor Networks (2006)
Newsome, J., Shi, E., Song, D., Perrig, A.: The Sybil Attack in Sensor Networks: Analysis & Defenses (2004)
Staniford-Chen, S., Cheng, S., Crawford, R., Dilger, M.: GRIDS – A Graph Based Intrusion Detection System for Large Networks. In: The 19th National Information Systems Security Conference (1996)
Brutch, P., Ko, C.: Challenges in intrusion detection for wireless sensor networks. In: Proceedings 2003 Symposium on Applications and the Internet Workshops, pp. 368–373 (2003)
Lancaster, H.O.: The chi-squared distribution. Wiley, Chichester (1969)
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Rong, C., Eggen, S., Cheng, H. (2011). An Efficient Intrusion Detection Scheme for Wireless Sensor Networks. In: Lee, C., Seigneur, JM., Park, J.J., Wagner, R.R. (eds) Secure and Trust Computing, Data Management, and Applications. STA 2011. Communications in Computer and Information Science, vol 187. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22365-5_15
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DOI: https://doi.org/10.1007/978-3-642-22365-5_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22364-8
Online ISBN: 978-3-642-22365-5
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