Abstract
Due to the resource limitations of sensor nodes, providing security protocols is a particular challenge in sensor networks. A popular proposed method is the neighborhood based key agreement protocol (NEKAP), which is an improvement over the well-known Localized Encryption and Authentication Protocol (LEAP). NEKAP is an efficient and light-weight protocol, but includes loopholes through which adversaries may launch replay attack by successfully masquerading as legitimate nodes and thereby compromise the communications over the network. In this paper, we present a modified security protocol for wireless sensor networks. Secure computation protocol for Naor-Reingold pseudorandom function was studied and a more efficient protocol was proposed based on multiplicative homomorphic encryption in this article. Based on the novel protocol, two private pattern matching protocol was designed. Also the improvement on the performance is discussed and analyzed on several typical attacks found in wireless sensor networks, i.e., replay attack. The performance verification through using a qualitative analysis indicates that our new security protocol can enhance the security resilience of wireless sensor networks better than the conventional methods.
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References
Zhibin, L.: An Intelligent WPICC Evaluation Model Based on DEA-ANN Hybrid Algorithm. Journal of Computational Information Systems 6(13), 4369–4377 (2010)
Lu, Z., Mian, C., Chen, L.I.: Software Behavior-Based Trusted Dynamic Measurement. Journal of Wuhan University (Natural Science Edition) 56(2), 133–137 (2010)
Lu, Z., Mian, C., Shen, C.: Trusted Dynamic Measurement Based on Interactive Markov Chains. Journal of Computer Research and Development, Chinese (8), 1464–1472 (2011)
Yang Xiaohui,Zhou Xuehai,Tian Junfeng et al. Novel Dynamic Trusted Evaluation Model of Software Behavior.Journal of Chinese Computer Systems, 31 (11),pp.2113-2120,2010.
Li, K., Gong, L., Kou, J.: Predicting software quality by fuzzy neural network based on rough set. Journal of Computational Information Systems 6(5), 1439–1448 (2010)
Li, Z., Wu, J., Wu, W.: Power customers load profile clustering using the SOM neural network. Automation of Electric Power Systems 32, 66–70 (2008)
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© 2014 Springer-Verlag Berlin Heidelberg
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Meng, M., Zhongwei, X., Yujun, Z. (2014). OPRF Secure Computation for Safety Neighbor Verification Protocols of Wireless Sensor Networks. In: Jeong, H., S. Obaidat, M., Yen, N., Park, J. (eds) Advances in Computer Science and its Applications. Lecture Notes in Electrical Engineering, vol 279. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41674-3_133
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DOI: https://doi.org/10.1007/978-3-642-41674-3_133
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41673-6
Online ISBN: 978-3-642-41674-3
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