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Correction published on 15 September 2022, see Appl. Sci. 2022, 12(18), 9233.
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Article

Profitable Double-Spending Attacks

School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), 123 Cheomdangwagi-ro, Buk-gu, Gwangju 61005, Korea
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Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(23), 8477; https://doi.org/10.3390/app10238477
Submission received: 9 November 2020 / Revised: 24 November 2020 / Accepted: 25 November 2020 / Published: 27 November 2020 / Corrected: 15 September 2022
(This article belongs to the Special Issue New Trends in Blockchain Technology)

Abstract

Our aim in this paper is to investigate the profitability of double-spending (DS) attacks that manipulate an a priori mined transaction in a blockchain. It was well understood that a successful DS attack is established when the proportion of computing power an attacker possesses is higher than that of the honest network. What is not yet well understood is how threatening a DS attack with less than 50% computing power used can be. Namely, DS attacks at any proportion can be a threat as long as the chance to make a good profit exists. Profit is obtained when the revenue from making a successful DS attack is greater than the cost of carrying out one. We have developed a novel probability theory for calculating a finitetime attack probability. This can be used to size up attack resources needed to obtain the profit. The results enable us to derive a sufficient and necessary condition on the value of a transaction targeted by a DS attack. Our result is quite surprising: we theoretically show how a DS attack at any proportion of computing power can be made profitable. Given one’s transaction value, the results can also be used to assess the risk of a DS attack. An example of profitable DS attack against BitcoinCash is provided.
Keywords: blockchain; double-spending attack; Fraud risk analysis; profitability; time-finite analysis; probability distribution; combinatorics blockchain; double-spending attack; Fraud risk analysis; profitability; time-finite analysis; probability distribution; combinatorics

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MDPI and ACS Style

Jang, J.; Lee, H.-N. Profitable Double-Spending Attacks. Appl. Sci. 2020, 10, 8477. https://doi.org/10.3390/app10238477

AMA Style

Jang J, Lee H-N. Profitable Double-Spending Attacks. Applied Sciences. 2020; 10(23):8477. https://doi.org/10.3390/app10238477

Chicago/Turabian Style

Jang, Jehyuk, and Heung-No Lee. 2020. "Profitable Double-Spending Attacks" Applied Sciences 10, no. 23: 8477. https://doi.org/10.3390/app10238477

APA Style

Jang, J., & Lee, H.-N. (2020). Profitable Double-Spending Attacks. Applied Sciences, 10(23), 8477. https://doi.org/10.3390/app10238477

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