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SCIENCE CHINA Information Sciences, Volume 60, Issue 4: 040305(2017) https://doi.org/10.1007/s11432-016-9028-0

A resilient trust management scheme for defending against reputation time-varying attacks based on BETA distribution

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  • ReceivedDec 7, 2016
  • AcceptedJan 23, 2017
  • PublishedMar 6, 2017

Abstract

Compared with the encryption and the authentication which can prevent the external attacks, the trust management schemes are the better approaches for defending against the internal attacks in wireless sensor network (WSN). The reputation time-varying (RTV) attacks are internal attacks. In the reputation time-varying attacks, the reputation value of nodes is manipulated to adjust dynamically by the compromised nodes or malicious attackers. Hence, these attacks have greater covert and invasive. In this paper, we propose a Time-window-based Resilient Trust Management Scheme (TRTMS) to defend against the reputation time-varying attacks in wireless sensor network. In this scheme, based on BETA distribution, the behaviors of compromised nodes are analyzed for a period of time, and then the difference judgment and the trend analysis are utilized to identify the abnormality of nodes' reputation value, meanwhile, the control factor $F_c$ and the time window are introduced to verify and remove the compromised modes from the suspected malicious nodes, which refer to those nodes' reputation value changes are caused by the wireless channel changes. The result of simulation shows that our proposed scheme can defend reputation time-varying attacks effectively and it is convenient to implement.


Acknowledgment

Acknowledgments

This work was partially supported by National Natural Science Foundation of China (Grant No. 61471346), Shanghai Natural Science Foundation (Grant No. 17ZR1429100), International Science and Technology Cooperation Program of China (Grant No. 2014DFA11640), National Program of International Science and Technology Cooperation (Grant No. 2014DFE10160), National Science and Technology Major Project (Grant No. 2014ZX03005001), and National Natural Science Foundation and Shanxi Provincial People's Government Jointly Funded Project of China for Coal Base and Low Carbon (Grant No. U1510115).


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