Skip to main content
SpringerLink
Log in

Self-adaptive trust management based on game theory in fuzzy large-scale networks

  • Methodologies and Application
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

Trust management plays an important role in ensuring and predicting the behaviors of nodes in networks. Most of the current trust management strategies adopt the average method to calculate nodes’ trust incomes and focus on two criteria (direct trust and recommendation). These strategies fail to consider the uncertainty in fuzzy and dynamic networks, and cannot effectively manage the low quality of information. In this paper, a novel trust management based on fuzzy logic and game theory by considering the uncertainty is established, which is appropriate for many different wireless networks (i.e., cognitive radio networks, social networking services, ad hoc networks, wireless mesh networks, and so on). First, we propose a multi-criteria fuzzy decision-making model to predict trust in the fuzzy and complex environment. Then a trust updating process based on game theory and evolutionary learning is designed. This process can self-adaptively adjust the trust evolution considering the dynamic of networks. Finally, two illustrative examples are provided to verify the proposed model. Compared to the traditional trust measurement method, the simulation results show that the proposed model has better adaptability and accuracy in fuzzy large-scale networks. More important, the proposed model achieves more significant performance gains over the traditional model.

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

Similar content being viewed by others

References

  • Al-Tous H, Barhumi I (2013) Joint power and band-width allocation for amplify-and-forward cooperative communications using Stackelberg game. IEEE Trans Veh Technol 62:1678–1691

  • Bernal R, Karanik M, Pelaez JI (2015) Fuzzy measure identification for criteria coalitions using linguistic information. Soft Comput. doi:10.1007/s00500-015-1589-5

  • Bharadwaj KK, Al-Shamri MYH (2009) Fuzzy computational models for trust and reputation systems. Electron Commer Res Appl 8:37–47

    Article  Google Scholar 

  • Chen L, Yan Z, Zhang W, Kantola R (2015) TruSMS: a trustworthy SMS spam control system based on trust management. Future Gener Comput Syst 49:77–93

    Article  Google Scholar 

  • Chen X, Huang J (2013) Evolutionary stable spectrum access. IEEE Trans Mob Comput 12:1281–1293

  • Esposito C, Ficco M, Palmieri F, Castiglione A (2015) Smart cloud storage service selection based on fuzzy logic, theory of evidence and game theory. IEEE Trans Comput. doi:10.1109/TC.2015.2389952

  • Geng Z, Zhu Q (2009) Rough set-based fuzzy rule acquisition and its application for fault diagnosis in petrochemical process. Ind Eng Chem Res 48:827–836

  • Lee Y, Li M, Yen T, Huang T (2011) Analysis of fuzzy decision making trial and evaluation laboratory on technology acceptance model. Expert Syst Appl 38:14407–14416

    Article  Google Scholar 

  • Li D, Liu C, Gan W (2009) A new cognitive model: cloud model. Int J Intell Syst 24:357–375

    Article  MATH  Google Scholar 

  • Lin CJ, Wu WW (2008) A causal analytical method for group decision-making under fuzzy environment. Expert Syst Appl 34:205–213

    Article  Google Scholar 

  • Liu KJR, Wang B (2012) Cognitive radio networking and security. Cambridge University Press, New York

  • Lopez J, Roman R, Agudo I, Fernandez GC (2010) Trust management systems for wireless sensor networks: best practices. Comput Commun 33:1086–1093

    Article  Google Scholar 

  • Luo J, Liu X, Fan M (2009) A trust model based on fuzzy recommendation for mobile ad-hoc networks. Comput Netw 53:2396–2407

    Article  MATH  Google Scholar 

  • Marmol FG, Prez GM (2010) Towards pre-standardization of trust and reputation models for distributed and heterogeneous systems. Comput Stand Interfaces 32:185–196

    Article  Google Scholar 

  • Opricovic S, Tzeng G (2003) Defuzzification within a multicaiteria decision model. Int J Uncertain Fuzziness Knowl Based Syst 11(5): 635–652. (0–419)

  • Papoulis A, Pillai SU (2002) Probability, random variables, and stochastic processes. McGraw-Hill, New York, pp 165–180

  • Rosaci D (2012) Trust measures for competitive agents. Knowl Based Syst 28:38–46

    Article  Google Scholar 

  • Roy A (2015) A novel multivariate fuzzy time series based forecasting algorithm incorporating the effect of clustering on prediction. Soft Comput. doi:10.1007/s00500-015-1619-3

  • Shatila H, Khedr M, Reed JH (2014) Opportunistic channel allocation decision making in cognitive radio communications. Int J Commun Syst 27:216–232

    Article  Google Scholar 

  • Shen Y, Yan Z, Kantola R (2014) Analysis on the acceptance of global trust management for unwanted traffic control based on game theory. Comput Secur 47:3–25

    Article  Google Scholar 

  • Tajeddine A, Kayssi A, Chehab A, Artail H (2011) Fuzzy reputation-based trust model. Appl Soft Comput 11:345–355

    Article  Google Scholar 

  • Wang J, Wu J, Wang J, Zhang H, Chen X (2015) Multi-criteria decision-making methods based on the Hausdorff distance of hesitant fuzzy linguistic numbers. Soft Comput. doi:10.1007/s00500-015-1609-5

  • Yahyaoui H (2012) A trrust-based game theoretical model for web services collaboration. Knowl Based Syst 27:162–169

    Article  Google Scholar 

  • Yao B, Hagras H, Alhaddad MJ, Alghazzawi D (2015) A fuzzy logic-based system for the automation of human behavior recognition using machine vision in intelligent environments. Soft Comput. doi:10.1007/s00500-014-1270-4

  • Yin G, Wang Y, Dong Y, Dong H (2013) Wright–Fisher multi-strategy trust evolution model with white noise for inter-network. Expert Syst Appl 40:7367–7380

    Article  Google Scholar 

  • Yu Y, Li K, Zhou W, Li P (2012) Trust mechanisms in wireless sensor networks: attack analysis and countermeasures. J Netw Comput Appl 35:867–880

    Article  Google Scholar 

  • Zadeh LA (2008) Is there a need for fuzzy logic? Inf Sci 178:2751–2779

    Article  MathSciNet  MATH  Google Scholar 

  • Zheng G, Krikidis I, Ottersten B (2013) Full-duplex cooperative cognitive radio with transmit imper fections. IEEE Trans Wirel Commun 12:2498–2511

Download references

Acknowledgments

The authors wish to thank the National Natural Science Foundation of China (NOs. 61072080, U1405255), Major Science and Technology Project in Fujian Province (No. 2014H61010105), Fujian Normal University Innovative Research Team (No. IRTL1207) and the Natural Science Foundation of Fujian Province (No. 2013J01222).

Author information

Authors and Affiliations

  1. Fujian Provincial Key Laboratory of Network Security and Cryptology, School of Mathematics and Computer Science, Fujian Normal University, Fuzhou, China

    He Fang, Li Xu & Xinyi Huang

Authors
  1. He Fang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Li Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xinyi Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Li Xu.

Additional information

Communicated by V. Loia.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fang, H., Xu, L. & Huang, X. Self-adaptive trust management based on game theory in fuzzy large-scale networks. Soft Comput 21, 907–921 (2017). https://doi.org/10.1007/s00500-015-1821-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-015-1821-3

Keywords

Search

Navigation