Skip to main content

Game Theoretic Analysis of Reputation Approach on Block Withholding Attack

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12570))

Abstract

Bitcoin and the underlying technology blockchain introduced an open distributed system that incorporates Proof of Work and Nakamoto Consensus. Despite the broad adoption by enthusiasts, the consensus mechanism is vulnerable to certain issues, such as block withholding attack, selfish mining, and 51% attack. Various solutions have been proposed to address these problems. RepuCoin is one successful example, which claims to solve the selfish mining and 51% attack by adopting a novel reputation concept and modified BFT protocol. We generalize the reputation concept introduced in RepuCoin, and implement it in traditional Bitcoin system to analyze whether it can prevent the block withholding attack. We propose a reputation-based reward mechanism for the Bitcoin blockchain and a reward sharing schema for the mining pools. We model the utility of honest mining and block withholding attack for pools, and find that the inclusion of reputation in Bitcoin’s reward mechanism and pools’ reward schema can prevent mining pools from launching block withholding attack.

The work has been partially supported by the Cyber Security Research Centre Limited whose activities are partially funded by the Australian Government’s Cooperative Research Centres Programme.

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   79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   99.99
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. Nakamoto, S.: Bitcoin: A peer-to-peer electronic cash system (2008)

    Google Scholar 

  2. Eyal, I., Sirer, E.G.: Majority is not enough: bitcoin mining is vulnerable. In: Christin, N., Safavi-Naini, R. (eds.) FC 2014. LNCS, vol. 8437, pp. 436–454. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-45472-5_28

    Chapter  Google Scholar 

  3. Rosenfeld, M.: Analysis of bitcoin pooled mining reward systems. arXiv preprint arXiv:1112.4980. (2011)

  4. Eyal, I.: The miner’s dilemma. In: 2015 IEEE Symposium on Security and Privacy, pp. 89–103. IEEE (2015)

    Google Scholar 

  5. Kwon, Y., Kim, D., Son, Y., Vasserman, E., Kim, Y.: Be selfish and avoid dilemmas: fork after withholding (faw) attacks on bitcoin. In: Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, Dallas, USA, pp. 195–209. ACM (2017)

    Google Scholar 

  6. Yu, J., Kozhaya, D., Decouchant, J., Esteves-Verissimo, P.: RepuCoin: your reputation is your power. IEEE Trans. Comput. 68(8), 1225–1237 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  7. Natoli, C., Yu, J., Gramoli, V., Esteves-Verissimo, P.: Deconstructing blockchains: A comprehensive survey on consensus, membership and structure. arXiv preprint arXiv:1908.08316. (2019)

  8. Pease, M., Shostak, R., Lamport, L.: Reaching agreement in the presence of faults. J. ACM (JACM) 27(2), 228–234 (1980)

    Article  MathSciNet  MATH  Google Scholar 

  9. Mui, L., Mohtashemi, M., Halberstadt, A.: Computational model of trust and reputation. In: Proceedings of the 35th Annual Hawaii International Conference on System Sciences, pp. 2431–2439. IEEE (2002)

    Google Scholar 

  10. Nash, J.: Non-cooperative games. Ann. Math., 286–295 (1951)

    Google Scholar 

  11. Courtois, N.T., Bahack, L.: On subversive miner strategies and block withholding attack in bitcoin digital currency. arXiv preprint arXiv:1402.1718. (2014)

  12. Kuchta, V., Zolotavkin, Y.: Detection constraint for harvesting attack in proof of work mining pools (2019)

    Google Scholar 

  13. Weerahandi, S.: Exact Statistical Methods for Data Analysis. Springer Science and Business Media, New York, USA (2003)

    MATH  Google Scholar 

  14. Nojoumian, M., Golchubian, A., Njilla, L., Kwiat, K., Kamhoua, C.: Incentivizing blockchain miners to avoid dishonest mining strategies by a reputation-based paradigm. In: Arai, K., Kapoor, S., Bhatia, R. (eds.) SAI 2018. AISC, vol. 857, pp. 1118–1134. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-01177-2_81

    Chapter  Google Scholar 

  15. Tang, C., Wu, L., Wen, G., Zheng, Z.: Incentivizing honest mining in blockchain networks: a reputation approach. IEEE Trans. Circuits Syst. II: Express Briefs 67(1), 117–121 (2019)

    Article  Google Scholar 

  16. Biryukov, A., Feher, D.: ReCon: sybil-resistant consensus from reputation. Pervasive Mobile Comput. 61, 101109 (2020)

    Article  Google Scholar 

  17. Zhuang, Q., Liu, Y., Chen, L., Ai, Z.: Proof of reputation: a reputation-based consensus protocol for blockchain based systems. In: Proceedings of the 2019 International Electronics Communication Conference, pp. 131–138 (2019)

    Google Scholar 

  18. Luu, L., Saha, R., Parameshwaran, I., Saxena, P., Hobor, A.: On power splitting games in distributed computation: The case of bitcoin pooled mining. In: 2015 IEEE 28th Computer Security Foundations Symposium, Verona, Italy, pp. 397–411. IEEE (2015)

    Google Scholar 

  19. Wood, G.: Ethereum: a secure decentralised generalised transaction ledger. Ethereum Project Yellow Paper 151(2014), 1–32 (2014)

    Google Scholar 

  20. Monero.: Moneropedia. https://web.getmonero.org/resources/moneropedia/

  21. Schrijvers, O., Bonneau, J., Boneh, D., Roughgarden, T.: Incentive compatibility of bitcoin mining pool reward functions. In: Grossklags, J., Preneel, B. (eds.) FC 2016. LNCS, vol. 9603, pp. 477–498. Springer, Heidelberg (2017). https://doi.org/10.1007/978-3-662-54970-4_28

    Chapter  Google Scholar 

  22. Leonardos, N., Leonardos, S., Piliouras, G.: Oceanic games: centralization risks and incentives in blockchain mining. In: Pardalos, P., Kotsireas, I., Guo, Y., Knottenbelt, W. (eds.) Mathematical Research for Blockchain Economy. SPBE, pp. 183–199. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-37110-4_13

    Chapter  MATH  Google Scholar 

  23. Bag, S., Sakurai, K.: Yet another note on block withholding attack on bitcoin mining pools. In: Bishop, M., Nascimento, A.C.A. (eds.) ISC 2016. LNCS, vol. 9866, pp. 167–180. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-45871-7_11

    Chapter  Google Scholar 

  24. Bag, S., Ruj, S., Sakurai, K.: Bitcoin block withholding attack: analysis and mitigation. IEEE Trans. Inf. Forensics Secur. 12(8), 1967–1978 (2016)

    Article  Google Scholar 

  25. Chen, Z., Li, B., Shan, X., Sun, X., Zhang, J.: Discouraging Pool Block Withholding Attacks in Bitcoins. arXiv preprint arXiv:2008.06923 (2020)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lianyang Yu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yu, L., Yu, J., Zolotavkin, Y. (2020). Game Theoretic Analysis of Reputation Approach on Block Withholding Attack. In: Kutyłowski, M., Zhang, J., Chen, C. (eds) Network and System Security. NSS 2020. Lecture Notes in Computer Science(), vol 12570. Springer, Cham. https://doi.org/10.1007/978-3-030-65745-1_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-65745-1_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-65744-4

  • Online ISBN: 978-3-030-65745-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics