Hostname: page-component-8448b6f56d-jr42d Total loading time: 0 Render date: 2024-04-24T15:24:07.520Z Has data issue: false hasContentIssue false
  • English
  • Français

BLOCKCHAIN DOUBLE-SPEND ATTACK DURATION

Published online by Cambridge University Press:  21 May 2020

Mark Brown ,
Erol Peköz Open the ORCID record for Erol Peköz [Opens in a new window]  and
Sheldon Ross
Mark Brown
Affiliation:
Department of Statistics, Columbia University, New York, NY, USA E-mail: pekoz@bu.edu
Erol Peköz
Affiliation:
School of Business, Boston University, Boston, MA, USA
Sheldon Ross
Affiliation:
Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, CA, USA
Get access Rights & Permissions [Opens in a new window]

Abstract

Many cryptocurrencies including Bitcoin are susceptible to a so-called double-spend attack, where someone dishonestly attempts to reverse a recently confirmed transaction. The duration and likelihood of success of such an attack depends on the recency of the transaction and the computational power of the attacker, and these can be related to the distribution of time for counts from one Poisson process to exceed counts from another by some desired amount. We derive an exact expression for this distribution and show how it can be used to obtain efficient simulation estimators. We also give closed-form analytic approximations and illustrate their accuracy.

Keywords

applied probabilityreliability theory
Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 35 , Issue 4 , October 2021 , pp. 858 - 866
Copyright
Copyright © Cambridge University Press 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Bissian, G. & Levine, B. (2017). Bobtail: A proof-of-work target that minimizes blockchain mining variance. Accepted to appear in ISOC NDSS 2020.Google Scholar
2.Bowden, R., Keeler, P., Krzesinski, A.E., & Taylor, P.G. (2018). Block arrivals in the Bitcoin blockchain. https://arxiv.org/pdf/1801.07447.pdf.Google Scholar
3.Eyal, I. & Sirer, E.G. (2018). Majority is not enough: Bitcoin mining is vulnerable. Communications of the ACM 61(7): 95–102.CrossRefGoogle Scholar
4.Georgiadis, E. & Zeilberger, D. (2019). A combinatorial-probabilistic analysis of bitcoin attacks. Journal of Difference Equations and Applications 25(1): 56–63.CrossRefGoogle Scholar
5.Gofffard, P.-O. (2019). Fraud risk assessment within blockchain transactions. Advances in Applied Probability 51(2): 443–467.CrossRefGoogle Scholar
6.Grunspan, C. & Perez-Marco, R. (2018). Double spend races. International Journal of Theoretical and Applied Finance 21(8): 1850053.CrossRefGoogle Scholar
7.Hall, P. (1992). Principles of edgeworth expansion. In The bootstrap and edgeworth expansion. Springer Series in Statistics. New York, NY: Springer.CrossRefGoogle Scholar
8.Lin, I.-C. & Liao, T.-C. (2017). A survey of blockchain security issues and challenges. IJ Network Security 19(5): 653–659.Google Scholar
9.Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. https://bitcoin.org/bitcoin.pdf.Google Scholar
10.Narayanan, A., Bonneau, J., Felten, E., Miller, A., & Goldfeder, S (2016). Bitcoin and cryptocurrency technologies: A comprehensive introduction. Princeton, NJ: Princeton University Press.Google Scholar
11.Orcutt, M. (2019). Once hailed as unhackable, blockchains are now getting hacked. MIT Technology Review, February 19, 2019.Google Scholar
12.Ozisik, A.P., Andresen, G., Bissias, G., Houmansadr, A., & Levine, B.N. (2016). A secure, efficient, and transparent network architecture for bitcoin. UMass Amherst, Tech. Rep. UM-CS-2016.Google Scholar
13.Ozisik, A.P. & Levine, B.N. (2017). An explanation of Nakamoto's analysis of double-spend attacks. arXiv preprint arXiv:1701.03977.Google Scholar
14.Pinzon, C. & Rocha, C. (2016). Double-spend attack models with time advantange for bitcoin. Electronic Notes in Theoretical Computer Science 329: 79–103.CrossRefGoogle Scholar
15.Rosenfeld, M. (2012). Analysis of hashrate-based doublespending. https://www.bitcoil.co.il/Doublespend.pdf.Google Scholar
16.Ross, S. (2019). Introduction to probability models, 12th ed. Academic Press.Google Scholar
17.Saia, R., Carta, S., Reforgiato Recupero, D., & Fenu, G. (2019). Internet of entities (IoE): A blockchain-based distributed paradigm for data exchange between wireless-based devices. In Conference: 8th International Conference on Sensor Networks (SENSORNETS-2019), Prague, Czech Republic.Google Scholar
18.Wang, H., Zheng, Z., Xie, S., Dai, H.-N., & Chen, X. (2018). Blockchain challenges and opportunities: A survey. International Journal of Web and Grid Services 14(4): 352.CrossRefGoogle Scholar