Skip to main content

Privacy-Preserving and Co-utile Distributed Social Credit

  • Conference paper
  • First Online:
Combinatorial Algorithms (IWOCA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10765))

Included in the following conference series:

Abstract

Reputation is a powerful incentive for agents to abide by the prescribed rules of an interaction. In computer science, reputation can be phrased as being an artificial incentive that can turn into self-enforcing protocols that would not be such otherwise. Quite recently, China has announced a national reputation system that will be launched in the future under the name of social credit system. However, to be generalizable without damaging the privacy of citizens/agents, a reputation system must be decentralized and privacy-preserving. We present a peer-to-peer fully distributed reputation protocol in which the anonymity of both the scoring and the scored agents is maintained. At the same time, the reputation protocol itself is co-utile, that is, the rational option for all agents is to honestly fulfill their part in the protocol.

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

Access this chapter

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

Institutional subscriptions

Similar content being viewed by others

References

  1. Creemers, R.: China Copyright and Media, 15 March 2018. https://chinacopyrightandmedia.wordpress.com/about/

  2. Domingo-Ferrer, J., Farràs, O., Martínez, S., Sánchez, D., Soria-Comas, J.: Self-enforcing protocols via co-utile reputation management. Inf. Sci. 367–368, 159–175 (2016)

    Article  Google Scholar 

  3. Domingo-Ferrer, J., Martínez, S., Sánchez, D., Soria-Comas, J.: Co-utility: self-enforcing protocols for the mutual benefit of participants. Eng. Appl. Artif. Intell. 59, 148–158 (2017)

    Article  Google Scholar 

  4. Domingo-Ferrer, J., Sánchez, D., Soria-Comas, J.: Co-utility - self-enforcing collaborative protocols with mutual help. Prog. Artif. Intell. 5(2), 105–110 (2016)

    Article  Google Scholar 

  5. Hoffman, K., Zage, D., Nita-Rotaru, C.: A survey of attack and defense techniques for reputation systems. ACM Comput. Surv. 42(1) (2009). Article no. 1

    Article  Google Scholar 

  6. Kamvar, S.D., Schlosser, M.T., Garcia-Molina, H.: The EigenTrust algorithm for reputation management in P2P networks. In: Proceedings of the 12th International Conference on World Wide Web, pp. 640–651. ACM (2003)

    Google Scholar 

  7. Leyton-Brown, K., Shoham, Y.: Essentials of Game Theory: A Concise Multidisciplinary Introduction. Morgan and Claypool, San Rafael (2008)

    MATH  Google Scholar 

  8. Liu, K., Terzi, E.: Towards identity anonymization on graphs. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data - SIGMOD 2008, pp. 93–106. ACM (2008)

    Google Scholar 

  9. Marti, S., Garcia-Molina, H.: Taxonomy of trust: categorizing P2P reputation systems. Comput. Netw. 50(4), 472–484 (2006)

    Article  Google Scholar 

  10. Osborne, M., Rubinstein, A.: A Course in Game Theory. MIT Press, Cambridge (1994)

    MATH  Google Scholar 

  11. Singh, A., Liu, L.: TrustMe: anonymous management of trust relationships in decentralized P2P systems. In: Proceedings of the Third International Conference on Peer-to-Peer Computing (P2P 2003), pp. 142–149 (2003)

    Google Scholar 

  12. Hsu, S.: China’s new social credit system. The Diplomat, 10 May 2015. http://thediplomat.com/2015/05/chinas-new-social-credit-system/

  13. Zhou, R., Hwang, K., Cai, M.: GossipTrust for fast reputation aggregation in peer-to-peer networks. IEEE Trans. Knowl. Data Eng. 20(9), 1282–1295 (2008)

    Article  Google Scholar 

Download references

Acknowledgments and Disclaimer

Partial support to this work has been received from the Templeton World Charity Foundation (grant TWCF0095/AB60 “CO-UTILITY”), ARC (grant DP160100913), the European Commission (projects H2020-644024 “CLARUS” and H2020-700540 “CANVAS”), the Government of Catalonia (ICREA Acadèmia Prize) and the Spanish Government (projects TIN2014-57364-C2-1-R “SmartGlacis” and TIN 2015-70054-REDC). The author holds the UNESCO Chair in Data Privacy, but the views in this paper are the author’s own and are not necessarily shared by UNESCO.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Josep Domingo-Ferrer .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Domingo-Ferrer, J. (2018). Privacy-Preserving and Co-utile Distributed Social Credit. In: Brankovic, L., Ryan, J., Smyth, W. (eds) Combinatorial Algorithms. IWOCA 2017. Lecture Notes in Computer Science(), vol 10765. Springer, Cham. https://doi.org/10.1007/978-3-319-78825-8_30

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-78825-8_30

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-78824-1

  • Online ISBN: 978-3-319-78825-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics