Skip to main content

The Optimization Model of Trust for White-Washing

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9483))

Abstract

With the increase of trust recommendation in the network services and applications, a large number of corresponding attacks including white-washing attacks have emerged. This paper proposes a trust optimization model in recommendation system to counter the white-washing attacks. The proposed model first separates the white-washing nodes from other nodes by dividing the nodes into different groups. The grouping will limit the dubious white-washing nodes in the proposed model so as to take these nodes much more cost to become a normal node. Meanwhile, the normal interactions are not affected. Our experimental results show that the proposed model can insulate suspicious white-washing nodes effectively, and ensures the normal interaction activities among normal nodes at the same time. Thus, the proposed model can resist the white-washing attacks effectively.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Bilge, L., Strufe, T., Balzarotti, D., Kirda, E.: All your contacts are belong to us: automated identity theft attacks on social networks. In: Proceedings of the 18th international conference on World wide web, pp. 551–560. ACM (2009)

    Google Scholar 

  2. Jagatic, T.N., Johnson, N.A., Jakobsson, M., Menczer, F.: Social phishing. Commun. ACM 50, 94–100 (2007)

    Article  Google Scholar 

  3. Wang, X., Liu, L., Su, J.: Rlm: a general model for trust representation and aggregation. IEEE Trans. Serv. Comput. 5, 131–143 (2012)

    Article  Google Scholar 

  4. Malik, Z., Akbar, I., Bouguettaya, A.: Web services reputation assessment using a hidden markov model. In: Baresi, L., Chi, C.-H., Suzuki, J. (eds.) ICSOC-ServiceWave 2009. LNCS, vol. 5900, pp. 576–591. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  5. Yahyaoui, H.: A trust-based game theoretical model for Web services collaboration. Knowl.-Based Syst. 27, 162–169 (2012)

    Article  Google Scholar 

  6. Huang, K., Yao, J., Fan, Y., Tan, W., Nepal, S., Ni, Y., Chen, S.: Mirror, mirror, on the web, which is the most reputable service of them all? In: Basu, S., Pautasso, C., Zhang, L., Fu, X. (eds.) ICSOC 2013. LNCS, vol. 8274, pp. 343–357. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  7. Malik, Z., Bouguettaya, A.: Rateweb: reputation assessment for trust establishment among web services. VLDB J. Int. J. Very Large Data Bases 18, 885–911 (2009)

    Article  Google Scholar 

  8. Yahyaoui, H., Zhioua, S.: Bootstrapping trust of Web services based on trust patterns and Hidden Markov Models. Knowl. Inf. Syst. 37, 389–416 (2013)

    Article  Google Scholar 

  9. Huang, K., Liu, Y., Nepal, S., Fan, Y., Chen, S., Tan, W.: A novel equitable trustworthy mechanism for service recommendation in the evolving service ecosystem. In: Franch, X., Ghose, A.K., Lewis, G.A., Bhiri, S. (eds.) ICSOC 2014. LNCS, vol. 8831, pp. 510–517. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  10. Kudtarkar, A.M., Umamaheswari, S.: Avoiding white washing in P2P networks. In: First International Communication Systems and Networks and Workshops, 2009, COMSNETS 2009, pp. 1–4. IEEE (2009)

    Google Scholar 

  11. Chen, J., Lu, H., Bruda, S.D.: Analysis of feedbacks and ratings on trust merit for peer-to-peer systems. In: International Conference on E-Business and Information System Security, 2009, EBISS’09, pp. 1–5. IEEE (2009)

    Google Scholar 

  12. de Almeida, R.B., Natif, M., Augusto, J., da Silva, A.P.B., Vieira, A.B.: Pollution and whitewashing attacks in a P2P live streaming system: analysis and counter-attack. In: 2013 IEEE International Conference on Communications (ICC), pp. 2006–2010. IEEE (2013)

    Google Scholar 

  13. Wang, G., Gui, X.-L.: Selecting and trust computing for transaction nodes in online social networks. Jisuanji Xuebao (Chin. J. Comput.) 36, 368–383 (2013)

    MathSciNet  Google Scholar 

  14. Xiong, L., Liu, L.: Peertrust: supporting reputation-based trust for peer-to-peer electronic communities. IEEE Trans. Knowl. Data Eng. 16, 843–857 (2004)

    Article  Google Scholar 

Download references

Acknowledgement

This work is partly support by the Fundamental Research Funds for the Central Universities(No.NZ2015108), and the China Postdoctoral Science Foundation funded project(2015M571752), and the Jiangsu Planned Projects for Postdoctoral Research Funds (1402033C),and Open Project Foundation of Information Technology Research Base of Civil Aviation Administration of China(NO.CAAC-ITRB-201405).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhidan Wang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Wang, Z., Wang, J., Zhao, Y. (2015). The Optimization Model of Trust for White-Washing. In: Huang, Z., Sun, X., Luo, J., Wang, J. (eds) Cloud Computing and Security. ICCCS 2015. Lecture Notes in Computer Science(), vol 9483. Springer, Cham. https://doi.org/10.1007/978-3-319-27051-7_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-27051-7_15

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27050-0

  • Online ISBN: 978-3-319-27051-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics