access icon free Approach for modelling trust in cluster-based wireless ad hoc networks

In this study, the authors propose a cluster-based trust management model that efficiently detects the malicious nodes and restricts them to be on a route in wireless ad hoc networks. In contrast to previous works, the trust of a node is calculated using various trust attributes having substantial effect on reliable routing in the networks. In the proposed model, each node periodically predicts the value of each trust attribute about other nodes using autoregression. Subsequently, the direct trust is estimated using the weighted combination of trust attributes and it is fine tuned using proportional–integral model. All these recommendation trusts, from common neighbours, are collected and combined by the clusterhead to quantify the trust, and hence the routing is reliable and secure in the proposed model. Simulation results show that the proposed trust model provides better throughput and packet delivery ratio in presence of malicious nodes compared to other existing schemes.

Inspec keywords: autoregressive processes; telecommunication network routing; ad hoc networks; telecommunication security

Other keywords: proportional-integral model; malicious nodes; autoregression analysis; direct trust estimation; cluster-based wireless ad hoc networks; packet delivery ratio; trust modelling; cluster head; trust attributes; recommendation trusts; network reliable routing; cluster-based trust management model

Subjects: Other topics in statistics; Radio links and equipment; Communication network design, planning and routing

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
    5. 5)
    6. 6)
    7. 7)
    8. 8)
      • 4. Govindan, K., Mohapatra, P.: ‘Trust computations and trust dynamics in mobile ad hoc networks: a survey’. IEEE Communications Surveys and Tutorials, 2012, 14, (2), pp. 279298.
    9. 9)
      • 6. Yu, W., Kuo, T.S.: ‘Continuous-time indirect adaptive control of the electro-hydraulic servo systems’, IEEE Trans. Control Syst. Technol., 1997, 5, (2), pp. 163177 (doi: 10.1109/87.556022).
    10. 10)
      • 20. Cho, J.H., Swami, A., Chen, I.R.: ‘Modeling and analysis of trust management for cognitive mission-driven group communication systems in mobile ad hoc networks’. Proc. Int. Conf. on Computational Science and Engineering, 29–31 August 2009, pp. 641650.
    11. 11)
      • 9. Akaike, H.: ‘A new look at statistical model identification’, IEEE Trans. Autom. Control, 1974, 19, pp. 716723 (doi: 10.1109/TAC.1974.1100705).
    12. 12)
      • 22. Chiang, C.-C., Wu, H.-K., Liu, W., Gerla, M.: ‘Routing in clustered multihop, mobile wireless networks with fading channel’. IEEE Singapore Int. Conf. on Networks, SICON'97, April 1997, pp. 197211.
    13. 13)
      • 10. Gu, Y., Chakraborty, S.: ‘Control theory-based DVS for interactive 3d games’. Proc. 45th Annual Design Automation Conf., DAC’08, 2008, pp. 740745.
    14. 14)
      • 5. Box, G., Jenkins, G., Reinsel, G.: ‘Time series analysis: forecasting and control’ (Wiley, 2008).
    15. 15)
      • 17. Theodorakopoulos, G., Baras, J.S.: ‘On trust models and trust evaluation metrics for ad hoc networks’, IEEE JSAC, 2006, 24, pp. 318328.
    16. 16)
      • 12. Dempster, A.P.: ‘A generalization of Bayesian interface’, J. R. Stat. Soc., 1968, 30, pp. 205447.
    17. 17)
      • 11. Astrom, K., Hagglund, T.: ‘PID controllers: theory, design and tuning’, 1995.
    18. 18)
      • 3. Cho, J.-H., Swami, A., Chen, I.-R.: ‘Modeling and analysis of trust management with trust chain optimization in mobile ad hoc networks’, J. Netw. Comput. Appl., 2012, 35, (3), pp. 10011012 (doi: 10.1016/j.jnca.2011.03.016).
    19. 19)
      • 1. Ghosh, U., Datta, R.: ‘A secure dynamic IP configuration scheme for mobile ad hoc networks’, Ad Hoc Netw., 2011, 9, (7), pp. 13271342 (doi: 10.1016/j.adhoc.2011.02.008).
    20. 20)
      • 13. Shafer, G.: ‘A mathematical theory of evidence’ (Princeton University Press, 1976).
    21. 21)
      • 16. Virendra, M., Jadliwala, M., Chandrasekaran, M., Upadhyaya, S.: ‘Quantifying trust in mobile ad hoc networks’. Proc. IEEE KIMAS 2005, 2005, pp. 6571.
    22. 22)
      • 2. Yen, Y.S., Chang, R.S., Chao, H.C.: ‘Flooding-limited for multi-constrained quality-of-service routing protocol in mobile ad hoc networks’, Commun. IET, 2008, 2, (7), pp. 972981 (doi: 10.1049/iet-com:20070471).
    23. 23)
      • 19. Boukerche, A, Ren, Y.: ‘A security management scheme using a novel computational reputation model for wireless and mobile ad hoc networks’. Proc. Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems, 2008, pp. 8895.
    24. 24)
      • 21. Wang, X., Liu, L., Su, J.: ‘RLM: a general model for trust representation and aggregation’. IEEE Trans. Services Comput., 2012, 5, (1), pp. 131143.
    25. 25)
      • 8. Stoica, P., Friedlander, B., Sderstrom, T.: ‘Least-squares, Yule–Walker, and overdetermined Yule–Walker estimation of AR parameters: a Monte Carlo analysis of finite-sample properties’, Int. J. Control, 1986, 43, (1), pp. 1327 (doi: 10.1080/00207178608933446).
    26. 26)
      • 14. Yu, D., Frincke, D.: ‘Alert confidence fusion in intrusion detection systems with extended Dempster–Shafer theory’. Proc. ACMSE 2005, 2005, pp. 142147.
    27. 27)
      • 18. Balakrishnnan, V., Varadharajan, V., Tupakula, U.K., Lucs, P.: ‘Trust and recommendations in mobile ad hoc networks’. Proc. Tenth IEEE Int. Conf. Networking and Services, 2007, pp. 6469.
    28. 28)
      • 7. Chatterjee, P., Sengupta, I., Ghosh, S.: ‘A distributed trust model for securing mobile ad hoc networks’. IEEE/IFIP 8th Int. Conf. on Embedded and Ubiquitous Computing, 2010, pp. 818825.
    29. 29)
      • 15. Ghosh, T., Pissinou, N., Makki, K.: ‘Towards designing a trust routing solution in mobile ad hoc networks’, Mobile Netw. Appl., 2005, 10, pp. 985995 (doi: 10.1007/s11036-005-4454-4).
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