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Incentive Compatibility of Pay Per Last N Shares in Bitcoin Mining Pools

  • Yevhen Zolotavkin
  • Julian García
  • Carsten Rudolph
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10575)

Abstract

Pay per last N shares (PPLNS) is a popular pool mining reward mechanism on a number of cryptocurrencies, including Bitcoin. In PPLNS pools, miners may stand to benefit by delaying reports of found shares. This attack may entail unfair or inefficient outcomes. We propose a simple but general game theoretical model of delays in PPLNS. We derive conditions for incentive compatible rewards, showing that the power of the most powerful miner determines whether incentives are compatible or not. An efficient algorithm to find Nash equilibria is put forward, and used to show how fairness and efficiency deteriorate with inside-pool inequality. In pools where all players have comparable computational power incentives to deviate from protocol are minor, but gains may be considerable in pools where miner’s resources are unequal. We explore how our findings can be applied to ameliorate delay attacks by fitting real-world parameters to our model.

References

  1. 1.
    Bag, S., Ruj, S., Sakurai, K.: Bitcoin block withholding attack: analysis and mitigation. IEEE Trans. Inf. Forensics Secur. 12(8), 1967–1978 (2017)CrossRefGoogle Scholar
  2. 2.
    BCmonster: Mining statistics (2017). http://www.bcmonster.com/. Accessed 22 Mar 2017
  3. 3.
    Chávez, J.J.G., da Silva Rodrigues, C.K.: Automatic hopping among pools and distributed applications in the bitcoin network. In: 2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA), pp. 1–7, August 2016Google Scholar
  4. 4.
    Dziembowski, S.: Introduction to cryptocurrencies. In: Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, CCS 2015, pp. 1700–1701, NY, USA (2015). http://doi.acm.org/10.1145/2810103.2812704
  5. 5.
    Fisch, B.A., Pass, R., Shelat, A.: Socially optimal mining pools. ArXiv e-prints March 2017Google Scholar
  6. 6.
    Fudenberg, D., Tirole, J.: Game Theory, 11th edn. The MIT Press, Cambridge (1991)zbMATHGoogle Scholar
  7. 7.
    Gervais, A., Karame, G.O., Wüst, K., Glykantzis, V., Ritzdorf, H., Capkun, S.: On the security and performance of proof of work blockchains. In: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, CCS 2016, pp. 3–16, NY, USA (2016). http://doi.acm.org/10.1145/2976749.2978341
  8. 8.
    Kano pool: Pool payout (2017). https://kano.is/index.php?k=payout. Accessed Mar 23 2017
  9. 9.
    Lewenberg, Y., Bachrach, Y., Sompolinsky, Y., Zohar, A., Rosenschein, J.S.: Bitcoin mining pools: A cooperative game theoretic analysis. In: Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015, pp. 919–927, International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2015). http://dl.acm.org/citation.cfm?id=2772879.2773270
  10. 10.
    Morabito, V.: Business Innovation Through Blockchain, vol. 1. Springer International Publishing AG, Heidelberg (2017)CrossRefGoogle Scholar
  11. 11.
    Nakamoto, S.: Bitcoin: A peer-to-peer electronic cash system (2008). https://bitcoin.org/bitcoin.pdf. Accessed 29 Jan 2016
  12. 12.
    P2Pool: P2Pool bitcoin mining pool global statistics (2017). http://p2pool.org/stats/index.php. Accessed 19 Mar 2017
  13. 13.
    Peck, M.: A blockchain currency that beat s bitcoin on privacy [news]. IEEE Spectr. 53(12), 11–13 (2016)CrossRefGoogle Scholar
  14. 14.
    Rosenfeld, M.: Analysis of bitcoin pooled mining reward systems. arXiv preprint (2011). arXiv:1112.4980
  15. 15.
    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). doi: 10.1007/978-3-662-54970-4_28 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Yevhen Zolotavkin
    • 1
  • Julian García
    • 1
  • Carsten Rudolph
    • 1
  1. 1.Faculty of ITMonash UniversityClaytonAustralia

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