Skip to main content
SpringerLink
Log in

A Hybrid Trust Management Scheme for Wireless Sensor Networks

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Wireless sensor network (WSN) consists of wireless small sensor nodes deployed in the terrain for continuous observation of physical or environmental conditions. The data collected from the WSN is used for making decisions. The condition for making critical decision is to assure the trustworthiness of the data generated from sensor nodes. However, the approaches for scoring the sensed data alone is not enough in WSN since there is an interdependency between node and data item. If the overall trust score of the network is based on one trust component, then the network might be misguided. In this work, we propose the hybrid approach to address the issue by assigning the trust score to data items and sensor nodes based on data quality and communication trust respectively. The proposed hybrid trust management scheme (HTMS) detects the data fault with the help of temporal and spatial correlations. The correlation metric and provenance data are used to score the sensed data. The data trust score is utilized for making decision. The communication trust and provenance data are used to evaluate the trust score of intermediate nodes and source node. If the data item is reliable enough to make critical decisions, a reward is given by means of adding trust score to the intermediate nodes and source node. A punishment is given by reducing the trust score of the source and intermediate nodes, if the data item is not reliable enough to make critical decisions. Result shows that the proposed HTMS detects the malicious, faulty, selfish node and untrustworthy data.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  1. Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). A survey on sensor networks. IEEE Communications Magazine, 40(8), 102–114.

    Article  Google Scholar 

  2. Lopez, J., Roman, R., Agudo, I., & Fernandez-Gago, C. (2010). Trust management systems for wireless sensor networks: Best practices. Computer Communications, 33, 0140–3664.

    Article  Google Scholar 

  3. Lim, H. S., Moon, Y. S., & Bertino, E. (2010). Provenance-based trustworthiness assessment in sensor networks. In Proceedings of the Seventh International Workshop on Data Management for Sensor Networks (pp. 2–7). ACM.

  4. Bertino, E. (2015). Data trustworthiness—approaches and research challenges. In Data privacy management, autonomous spontaneous security, and security assurance (pp. 17–25). Springer: Cham. doi:10.1007/978-3-319-17016-9_2.

  5. Jiang, J., Han, G., Wang, F., Shu, L., & Guizani, M. (2015). An efficient distributed trust model for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 26(5), 1228–1237.

    Article  Google Scholar 

  6. Momani, M., Challa, S., & Alhmouz, R. (2010). Bayesian fusion algorithm for inferring trust in wireless sensor networks. Journal of Networks, 5(7), 815–822.

    Article  Google Scholar 

  7. Han, G., Jiang, J., Shu, L., Niu, J., & Chao, H. C. (2014). Management and applications of trust in wireless sensor networks: A survey. Journal of Computer and System Sciences, 80(3), 602–617.

    Article  MATH  Google Scholar 

  8. Karthik, N., & Ananthanarayana, V. S. (2016). Data trustworthiness in wireless sensor networks. In IEEE TrustCom/BigDataSE/ISPA. 2016.

  9. Fang, L., & Dobson, S. (2013). In-network sensor data modelling methods for fault detection. In International joint conference on ambient intelligence (pp. 176–189). Springer.

  10. Tolle, G., Polastre, J., Szewczyk, R., Culler, D., Turner, N., Tu, K., & Hong, W. (2005). A macroscope in the redwoods. In Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems (pp. 51–63). ACM.

  11. Kamal, A. R. M., Bleakley, C., & Dobson, S. (2013). Packet-level attestation (PLA): A framework for in-network sensor data reliability. ACM Transactions on Sensor Networks (TOSN), 9(2), 19.

    Article  Google Scholar 

  12. Sharma, A. B., Golubchik, L., & Govindan, R. (2010). Sensor faults: Detection methods and prevalence in real-world datasets. ACM Transactions on Sensor Networks (TOSN), 6(3), 23.

    Article  Google Scholar 

  13. Guestrin, C., Bodik, P., Thibaux, R., Paskin, M., & Madden, S. (2004). Distributed regression: an efficient framework for modeling sensor network data. In Information Processing in Sensor Networks, 2004. IPSN 2004. Third International Symposium on (pp. 1–10). IEEE.

  14. Jadidoleslamy, H., Aref, M. R., & Bahramgiri, H. (2016). A fuzzy fully distributed trust management system in wireless sensor networks. AEU-International Journal of Electronics and Communications, 70(1), 40–49.

    Article  Google Scholar 

  15. Won, J., & Bertino, E. (2015). Distance-based trustworthiness assessment for sensors in wireless sensor networks. In International Conference on Network and System Security (pp. 18–31). Springer.

  16. Hur, J., Lee, Y., Youn, H., Choi, D., & Jin, S. (2005). Trust evaluation model for wireless sensor networks. In The 7th International Conference on Advanced Communication Technology, 2005, ICACT 2005 (Vol. 1, pp. 491–496). IEEE.

  17. Xiao, X. Y., Peng, W. C., Hung, C. C., & Lee, W. C. (2007 June). Using sensorranks for in-network detection of faulty readings in wireless sensor networks. In Proceedings of the 6th ACM International Workshop on Data Engineering for Wireless and Mobile Access (pp. 1–8). ACM.

  18. Shaikh, R. A., Jameel, H., d’Auriol, B. J., Lee, H., Lee, S., & Song, Y. J. (2009). Group-based trust management scheme for clustered wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 20(11), 1698–1712.

    Article  Google Scholar 

  19. Dhulipala, V. R. S. & Karthik, N. (2017). Trust management technique in wireless sensor networks: Challenges and issues for reliable communication: A review. CSIT. doi:10.1007/s40012-017-0169-5.

  20. Talbi, S., Koudil, M., & Bouabdallah, A., et al. (2016). Adaptive and dual data-communication trust scheme for clustered wireless sensor networks. Telecommunication Systems. doi:10.1007/s11235-016-0254-3.

  21. Dogan, G., & Avincan, K. (2016). MultiProTru: A Kalman filtering based trust architecture for two-hop wireless sensor networks. Peer-to-Peer Networking and Applications, 1, 1–14.

    Google Scholar 

  22. Zhang, B., Huang, Z., & Xiang, Y. (2014). A novel multiple-level trust management framework for wireless sensor networks. Computer Networks, 72, 45–61.

    Article  Google Scholar 

  23. Li, X., Zhou, F., & Du, J. (2013). LDTS: A lightweight and dependable trust system for clustered wireless sensor networks. IEEE Transaction on Information Forensics and Security, 8(6), 924–935.

    Article  Google Scholar 

  24. Sun, Y., Luo, H., & Das, S. K. (2012). A trust-based framework for fault-tolerant data aggregation in wireless multimedia sensor networks. IEEE Transactions on Dependable and Secure Computing, 9(6), 785–797.

    Article  Google Scholar 

  25. Wang, G., & Wu, J. (2011). Multi-dimensional evidence-based trust management with multi-trusted paths. Future Generation Computer Systems, 27(5), 529–538.

    Article  Google Scholar 

  26. Aivaloglou, E., & Gritzalis, S. (2010). Hybrid trust and reputation management for sensor networks. Wireless Networks, 16(5), 1493–1510.

    Article  Google Scholar 

  27. Zhang, J. et al. (2010). A trust management architecture for hierarchical wireless sensor networks. In IEEE 35th Conference on. Local Computer Networks (LCN).

  28. Karthik, N., & Ananthanarayana, V. S. (2017). Data trust model for event detection in wireless sensor networks using data correlation techniques. In IEEE 4th Conference on Signal Processing, Communications and Networking (In press).

  29. Dhulipala, V. S., Karthik, N., & Chandrasekaran, R. M. (2013). A novel heuristic approach based trust worthy architecture for wireless sensor networks. Wireless Personal Communications, 70(1), 189–205.

    Article  Google Scholar 

  30. Karthik, N., & Dhulipala, V. R. S. (2011). Trust calculation in wireless sensor networks. In 3rd IEEE, International Conference on Electronics Computer Technology.

  31. Zhang, Y., Meratnia, N., & Havinga, P. (2010). Outlier detection techniques for wireless sensor networks: A survey. IEEE Communications Surveys and Tutorials, 12(2), 159–170.

    Article  Google Scholar 

  32. He, D., Chen, C., Chan, S., Bu, J., & Vasilakos, A. V. (2012). ReTrust: Attack-resistant and lightweight trust management for medical sensor networks. IEEE Transactions on Information Technology in Biomedicine, 16(4), 623–632.

    Article  Google Scholar 

  33. Schnbrodt, F. D., & Perugini, M. (2013). At what sample size do correlations stabilize? Journal of Research in Personality, 47(5), 609–612.

    Article  Google Scholar 

  34. Sensorscope project. http://sensorscope.epfl.ch/.

  35. Nguyen, T. A., Bucur, D., Aiello, M., & Tei, K. (2013). Applying time series analysis and neighbourhood voting in a decentralised approach for fault detection and classification in WSNs. In Proceedings of the Fourth Symposium on Information and Communication Technology (pp. 234–241). ACM.

  36. Yao, Y., Sharma, A., Golubchik, L., & Govindan, R. (2010). Online anomaly detection for sensor systems: A simple and efficient approach. Performance Evaluation, 67(11), 1059–1075.

    Article  Google Scholar 

  37. De Meulenaer, G., Gosset, F., Standaert, F. X., & Pereira, O. (2008). On the energy cost of communication and cryptography in wireless sensor networks. In 2008 IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (pp. 580–585). IEEE.

  38. Pires, W. R., de Paula Figueiredo, T. H., Wong, H. C., & Loureiro, A. A. F. (2004). Malicious node detection in wireless sensor networks. In Parallel and Distributed Processing Symposium, 2004. Proceedings. 18th International (p. 24). IEEE.

  39. https://en.wikipedia.org/wiki/Peukert%27s_law.

  40. Yao, Z., Kim, D., & Doh, Y. (2006). PLUS: Parameterized and localized trust management scheme for sensor networks security. In 2006 IEEE International Conference on Mobile Ad Hoc and Sensor Systems (pp. 437–446). IEEE.

Download references

Author information

Authors and Affiliations

  1. Department of Information Technology, National Institute of Technology Karnataka, Mangalore, India

    N. Karthik & V. S. Ananthanarayana

Authors
  1. N. Karthik
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. V. S. Ananthanarayana
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to N. Karthik.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Karthik, N., Ananthanarayana, V.S. A Hybrid Trust Management Scheme for Wireless Sensor Networks. Wireless Pers Commun 97, 5137–5170 (2017). https://doi.org/10.1007/s11277-017-4772-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-017-4772-4

Keywords

Search

Navigation