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Wireless Networks

, Volume 22, Issue 7, pp 2239–2257 | Cite as

Applying trust enhancements to reactive routing protocols in mobile ad hoc networks

  • Hui XiaEmail author
  • Jia Yu
  • Zhen-kuan Pan
  • Xiang-guo Cheng
  • Edwin H. -M. Sha
Article

Abstract

Due to the characteristics of mobile ad hoc networks, such networks are more susceptible to the destruction of malicious attacks or denial of cooperation. It would be easy for an adversary or a malicious node to launch attacks on routing function, especially attacks on packet routing. In order to mitigate these hazards, we incorporate the concept of ‘trust’ into MANETs, and abstract a decentralized trust inference model. The core of this model is trust computation, which is divided into two parts: historical trust assessment and trust prediction. We can quantify a node’s historical trust based on its historical behaviors via introducing multiple trust attributes. The fuzzy AHP method based on entropy weights is used to calculate the weight of trust attributes. By making use of the obtained historical trust data sequence, we propose an improved dynamic grey-Markov chain prediction measure to effectively estimate node’s trust prediction. In order to verify the validity of our trust model, we propose a trust-enhanced unicast routing protocol and a trust-enhanced multicast routing protocol, respectively. Both of the two new protocols can provide a feasible approach to kick out the untrustworthy nodes and choose the optimal trusted routing path. Moreover, the new proposed data-driven route maintenance mechanisms can reduce the routing overhead. The persuasive experiments have been conducted to evaluate the effectiveness of the new proposed trust-enhanced routing protocols in the aspects of packets delivery ratio, end-to-end latency, malicious node detection and attack resistance.

Keywords

Mobile ad hoc network Malicious node Decentralized trust inference model Trust-enhanced routing protocol Data-driven route maintenance mechanism 

Notes

Acknowledgement

We would like to thank anonymous referees for their helpful suggestions to improve this paper. This research is sponsored by the Natural Science Foundation of China (NSFC) under Grant Nos. 61402245, 61572267 and 61272425, the Project funded by China Postdoctoral Science Foundation under Grand Nos. 2015T80696 and 2014M551870, the Shandong Provincial Natural Science Foundation No. ZR2014FQ010, the Project funded by Qingdao Postdoctoral Science Foundation, the Open Project Foundation of Shandong Provincial Key Laboratory of Software Engineering under Grant No. 2013SE01, PAPD, CICAEET and Foundation of Huawei under Grant No. YB2013120027. And it is partially supported by NSF CNS-1015802, HK GRF 123609, China Thousand-Talent Program, China National 863 Program 2013AA013202.

References

  1. 1.
    Govindan, K., & Mohapatra, P. (2012). Trust computations and trust dynamics in mobile adhoc networks: A survey. IEEE Communications Surveys and Tutorials, 14(2), 279–298.CrossRefGoogle Scholar
  2. 2.
    Li, W., Parker, J., & Joshi, A. (2012). Security through collaboration and trust in MANETs. Mobile Networks and Applications, 17(3), 342–352.CrossRefGoogle Scholar
  3. 3.
    Liang, Z., & Shi, W. (2008). Analysis of ratings on trust inference in open environments. Performance Evaluation, 65(2), 99–128.CrossRefGoogle Scholar
  4. 4.
    Onolaja, O., Bahsoon, R., & Theodoropoulos, G. (2011). Trust dynamics: A data-driven simulation approach. Trust Management V, 358, 323–334.Google Scholar
  5. 5.
    Zhang, F., Jia, Z., Xia, H., Li, X., & Sha, E. (2012). Node trust evaluation in mobile ad hoc networks based on multi-dimensional fuzzy and Markov SCGM(1,1) model. Computer Communications, 35(5), 589–596.CrossRefGoogle Scholar
  6. 6.
    Xia, H., Jia, Z., Li, X., Ju, L., & Sha, E. (2013). Trust prediction and trust-based source routing in mobile ad hoc networks. Ad Hoc Networks, 11(7), 2096–2114.CrossRefGoogle Scholar
  7. 7.
    Marchang, N., & Datta, R. (2012). Light-weight trust-based routing protocol for mobile ad hoc networks. IET-Information Security, 6(2), 77–83.CrossRefGoogle Scholar
  8. 8.
    Eissa, T., Razak, S., & Khokhar, R. (2013). Trust-based routing mechanism in MANET: Design and implementation. Mobile Networks and Applications, 18(5), 666–677.CrossRefGoogle Scholar
  9. 9.
    Xia, H., Jia, Z., Li, X., Ju, L., & Sha, E. (2013). Impact of trust model on on-demand multi-path routing in mobile ad hoc networks. Computer Communications, 36(9), 1078–1093.CrossRefGoogle Scholar
  10. 10.
    Cho, J., & Chen, I. (2013). On the tradeoff between altruism and selfishness in MANET trust management. Ad Hoc Networks, 11(8), 2217–2234.CrossRefGoogle Scholar
  11. 11.
    Mohanapriya, M., & Krishnamurthi, I. (2014). Trust based DSR routing protocol for mitigating cooperative black hole attacks in ad hoc networks. Arabian Journal for Science and Engineering, 39(3), 1825–1833.CrossRefGoogle Scholar
  12. 12.
    Xia, H., Jia, Z., & Sha, E. (2014). Research of trust model based on fuzzy theory in mobile ad hoc networks. IET-Information Security, 8(2), 88–103.CrossRefGoogle Scholar
  13. 13.
    Mitchell, R., & Chen, I. (2014). A survey of intrusion detection in wireless network applications. Computer Communications, 42, 1–23.CrossRefGoogle Scholar
  14. 14.
    Rahimi, M., & Riazi, A. (2014). On local entropy of fuzzy partitions. Fuzzy Sets and Systems, 234, 97–108.MathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Wu, Gin-Der, & Zhu, Zhen-Wei. (2014). An enhanced discriminability recurrent fuzzy neural network for temporal classification problems. Fuzzy Sets and Systems, 237, 47–62.MathSciNetCrossRefzbMATHGoogle Scholar
  16. 16.
    Zhang, L. X., & Lam, J. (2010). Necessary and sufficient conditions for analysis and synthesis of Markov jump linear systems with incomplete transition descriptions. IEEE Transactions on Automatic Control, 55(7), 1695–1701.MathSciNetCrossRefGoogle Scholar
  17. 17.
    Xie, Y. H., Hu, J. K., Xiang, Y. H., Yu, S., Tang, S. S., & Wang, Y. (2013). Modeling oscillation behavior of network traffic by nested hidden Markov model with variable state-duration. IEEE Transactions on Parallel and Distributed Systems, 24(9), 1807–1817.CrossRefGoogle Scholar
  18. 18.
    Marina, M. K. & Das, S. R.(2001). On-demand multipath distance vector routing for ad hoc networks. In Proceedings of international conference on network protocols, Riverside, CA, USA (pp. 11–14). November 2001.Google Scholar
  19. 19.
    Manvi, S. S., & Kakkasageri, M. S. (2008). Multicast routing in mobile ad hoc networks by using a multiagent system. Information Sciences, 178(6), 1611–1628.MathSciNetCrossRefGoogle Scholar
  20. 20.
    ‘NS-2’. http://www.isi.edu/nsnam/ns/. Accessed December 2012.
  21. 21.
    Shen, J., Tan, H. W., Wang, J., Wang, J. W., & Lee, S. (2015). A novel routing protocol providing good transmission reliability in underwater sensor networks. Journal of Internet Technology, 16(1), 171–178.Google Scholar
  22. 22.
    Xie, S. D., & Wang, Y. X. (2014). Construction of tree network with limited delivery latency in homogeneous wireless sensor networks. Wireless Personal Communications, 78(1), 231–246.CrossRefGoogle Scholar
  23. 23.
    Chen, I. R., Bao, F. Y., Chang, M., & Cho, J. H. (2014). Dynamic trust management for delay tolerant networks and its application to secure routing. IEEE Transactions on Parallel and Distributed Systems, 25(5), 1200–1210.CrossRefGoogle Scholar
  24. 24.
    Zhao, H. Y., Yang, X., & Li, X. L. (2013). cTrust: Trust management in cyclic mobile ad hoc networks. IEEE Transactions on Vehicular Technology, 62(6), 2792–2806.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Hui Xia
    • 1
    • 2
    • 3
    Email author
  • Jia Yu
    • 1
    • 4
  • Zhen-kuan Pan
    • 1
    • 2
  • Xiang-guo Cheng
    • 1
    • 2
  • Edwin H. -M. Sha
    • 5
  1. 1.College of Information EngineeringQingdao UniversityQingdaoPeople’s Republic of China
  2. 2.Postdoctoral Research Station of System ScienceQingdao UniversityQingdaoPeople’s Republic of China
  3. 3.Shandong Provincial Key Laboratory of Software EngineeringShandong UniversityJinanPeople’s Republic of China
  4. 4.School of Computer and SoftwareNanjing University of Information Science and TechnologyNanjingPeople’s Republic of China
  5. 5.Department of Computer ScienceUniversity of TexasDallasUSA

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