A Lightweight and Dependable Trust Model for Clustered Wireless Sensor Networks

  • Nannan ShaoEmail author
  • Zhiping Zhou
  • Ziwen Sun
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9483)


The resource efficiency and dependability are the most basic requirements for a trust model in any wireless sensor network. However, owing to high cost and low reliability, the existing trust models for wireless sensor networks can not satisfy these requirements. To take into account the issues, a lightweight and dependable trust model for clustered wireless sensor network is proposed in this paper, in which the fuzzy degree of nearness is adopted to evaluate the reliability of the recommended trust values from the third party nodes. Moreover, the definition of a self-adapted weighted method for trust aggregation at CH level surpasses the limitations of the subjective definition of weights in traditional weighted method. Theoretical analysis and simulation results show, compared with other typical trust models, the proposed scheme requires less memory and communication overhead and has good fault tolerance and robustness, which can effectively guarantee the security of wireless sensor network.


Wireless sensor networks Trust model Clustered wireless sensor network Fuzzy degree of nearness Self-adapted weighted method 



The paper is supported by the Nature Science Foundation of Jiangsu Province (No. BK20131107).


  1. 1.
    Khalid, O., Khan, S.U., Madani, S.A., et al.: Comparative study of trust and reputation systems for wireless sensor networks. Secur. Commun. Netw. 6, 669–688 (2013)CrossRefGoogle Scholar
  2. 2.
    Kant, K.: Systematic design of trust management systems for wireless sensor networks: a review. In: 4th IEEE International Conference on Advanced Computing and Communication Technologies (ACCT), pp. 208–215 (2014)Google Scholar
  3. 3.
    Ishmanov, F., Malik, A.S., Kim, S.W., et al.: Trust management system in wireless sensor networks: design considerations and research challenges. Trans. Emerg. Telecommun. Technol. 26, 107–130 (2015)CrossRefGoogle Scholar
  4. 4.
    Ganeriwal, S., Balzano, L.K., Srivastava, M.B.: Reputation-based framework for high integrity sensor networks. ACM Trans. Sensor Netw. (TOSN) 4, 15 (2008)Google Scholar
  5. 5.
    Yao, L., Wang, D., Liang, X., et al.: Research on multi-level fuzzy trust model for wireless sensor networks. Chin. J. Sci. Instru. 35, 1606–1613 (2014)Google Scholar
  6. 6.
    Duan, J., Gao, D., Yang, D., et al.: An energy-aware trust derivation scheme with game theoretic approach in wireless sensor networks for IoT applications. IEEE Internet Things J. 1, 58–69 (2014)CrossRefGoogle Scholar
  7. 7.
    Zhang, M., Xu, C., Guan, J., et al.: A novel bio-inspired trusted routing protocol for mobile wireless sensor networks. KSII Trans. Internet Inf. Syst. (TIIS). 8, 74–90 (2014)CrossRefGoogle Scholar
  8. 8.
    Boukerche, A., Xu, L., EL-Khatib, K.: Trust-based Security for wireless Ad Hoc and sensor networks. Comput. Commun. 30, 2413–2427 (2007)CrossRefGoogle Scholar
  9. 9.
    Shaikh, R.A., Jameel, H., d’Auriol, B.J., et al.: Group-based trust management scheme for clustered wireless sensor networks. IEEE Trans. Parallel Distrib. Syst. 20, 1698–1712 (2009)CrossRefGoogle Scholar
  10. 10.
    Bao, F., Chen, R., Chang, M.J., et al.: Hierarchical trust management for wireless sensor networks and its applications to rrust-based routing and intrusion detection. IEEE Trans. Netw. Serv. Manage. 9, 169–183 (2012)CrossRefGoogle Scholar
  11. 11.
    Li, X., Zhou, F., Du, J.: LDTS: a lightweight and dependable trust system for clustered wireless sensor networks. IEEE Trans. Inf. Forensics Secur. 8, 924–935 (2013)CrossRefGoogle Scholar
  12. 12.
    Younis, O., Fahmy, S.: HEED: a hybrid, energy-efficient, distributed clustering approach for ad-hoc sensor networks. IEEE Trans. Mob. Comput. 3, 366–379 (2004)CrossRefGoogle Scholar
  13. 13.
    Wei, D., Jin, Y., Vural, S., et al.: An energy-efficient clustering solution for wireless sensor networks. IEEE Trans. Wireless Commun. 10, 3973–3983 (2011)CrossRefGoogle Scholar
  14. 14.
    Javaid, N., Qureshi, T.N., Khan, A.H., et al.: EDDEEC: enhanced developed distributed energy-efficient clustering for heterogeneous wireless sensor networks. Procedia Comput. Sci. 19, 914–919 (2013)CrossRefGoogle Scholar
  15. 15.
    Han, G., Jiang, J., Shu, L., et al.: Management and applications of trust in wireless sensor networks: a survey. J. Comput. Syst. Sci. 80, 602–617 (2014)zbMATHCrossRefGoogle Scholar
  16. 16.
    Yang, J., Gong, F.: Consistent and reliable fusion method of multi-sensor based on degree of nearness. Chin. J. Sens. Actuators 23, 984–988 (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.School of Internet of Things EngineeringJiangnan UniverstiyWuxiChina

Personalised recommendations