Abstract
As many wireless sensor networks (WSNs) are deployed in complicated environment without good physical protection, the sensor nodes are more vulnerable to be affected by uncertain factors from inside or outside so that the sensed data always cannot reflect the real world situation well. Thus the trustworthiness of sensor nodes should be evaluated for revising the faulty ones in after-deployment maintenances. In this paper, we propose a trustworthiness evaluation method based on D-S evidence theory in data level for sensor nodes which can sense multi-dimensional data. Different dimensions of a sensor node are regarded as its different trustworthiness attributes in this method. For a single node, the trustworthiness of each attribute is evaluated firstly based on evidence theory, and then the lower and upper limits of trust degree for this node are calculated by fusing the evaluation results of different attributes. Moreover, in order to figure out whether regional uncertain factors exist or not, the trust degree of a local region is given by fusing the judgments of deployed sensor nodes according to the combination rules of evidence theory. Extensive experiments based on actual data samples are conducted to evaluate the performance of our method. The theoretical analysis and experimental results show that our method can give effective trustworthiness evaluation for one single sensor node or a local region. Also, robustness and stability of this method are verified in the experiments.
Keywords
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References
Tolle, G., Polastre, J., Szewczyk, R., Turner, N., Tu, K., Burgess, S., Gay, D.: A Macroscope in the Redwoods. In: SenSys. 2005 (2005)
Xing, K., Liu, F., Cheng, X., Du, D.H.C.: Real-time detection of clone attacks in wireless sensor networks. In: Proceedings of IEEE ICDCS, Beijing, China (2008)
Magistretti, E., Gurewitz, O., Knightly, E.: Inferring and mitigating a links hindering transmissions in managed 802.11 wireless networks. In: Proceedings of ACM MobiCom, Chicago, Illinois, USA (2010)
Wang, X., Fu, L., Hu, C.: Multicast performance with hierarchical cooperation. IEEE/ACM Transactions on Networking 20, 917–930 (2011)
He, T., et al.: VigilNet. An Integrated Sensor Network System for Energy-Efficient Surveillance. ACM Transactions on Sensor Networks 2, 1–38 (2006)
Dempster: Upper and lower probabilities induced by multivalued mapping. Annals of Mathematical Statistics 38(2), 325–339 (1967)
Shafer, Glenn: A Mathematical Theory of Evidence. Princeton University Press (1976)
Momani, M., Challa, S., Alhmouz, R.: Bayesian Fusion Algorithm for Inferring Trust in Wireless Sensor Networks. Journal of Networks 5(7) (July 2010)
Ma, Q., Liu, K., Miao, X., Liu, Y.: Sherlock is Around: Detecting Network Failures with Local Evidence Fusion. In: INFOCOM (2012)
Momani, M., Aboura, K., Challa, S.: RBATMWSN. Recursive Bayesian Approach to Trust Management in Wireless Sensor Networks. In: The Third International Conference on Intelligent Sensors, Sensor Networks and Information, Melbourne, Australia (2007)
Ba, S., Pavlou, P.A.: Evidence of the effect of trust building technology in electronic markets: price premiums and buyer behavior. MIS Quarterly 26 (2002)
Marsh, S.: Formalising Trust as a Computational Concept. In: Departmet of Computer Science and Mathematics. PhD, University of Stirling, p. 184 (1994)
McKnight, D.H., Chervany, N.L.: Conceptualizing Trust: A Typology and Ecommerce Customer Relationships Model. Presented at Proceedings of the 34th Hawaii International Conference on System Sciences (2001)
Srinivasan, A., Teitelbaum, J., Wu, J.: DRBTS. Distributed Reputation-based Beacon Trust System. In: 2nd IEEE International Symposium on Dependable, Autonomic and Secure Computing (2006)
Li, N.H., Mitchell, J.C., Winsborough, W.H.: Beyond Proof-of-Compliance: Security Analysis in Trust Management. J. ACM 52, 474–514 (2005)
Marmol, F.G., Perez, G.M.: Towards Pre-standardization of Trust and Reputation Models for Distributed and Heterogeneous Systems. Comput. Stand. Interfaces 32, 185–196 (2010)
Lopez, J., Roman, R., Agudo, I.: Trust Management Systems for Wireless Sensor Networks: Best Practices. Comput. Commun. 33, 1086–1093 (2010)
Li, J.L., Gu, L.Z., Yang, Y.X.: A New Trust Management Model for P2P Networks with Time Self-Decay and Subjective Expect. J. Electron. Inf. Technol. 31, 2786–2790 (2009)
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Miao, C., Huang, L., Guo, W., Xu, H. (2013). A Trustworthiness Evaluation Method for Wireless Sensor Nodes Based on D-S Evidence Theory. In: Ren, K., Liu, X., Liang, W., Xu, M., Jia, X., Xing, K. (eds) Wireless Algorithms, Systems, and Applications. WASA 2013. Lecture Notes in Computer Science, vol 7992. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39701-1_14
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DOI: https://doi.org/10.1007/978-3-642-39701-1_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39700-4
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