Analysis of Bitcoin Fork by Colored Petri Nets

Bitcoin is under the threat of fork since it operates with a distributed ledger. Predicting the fork probability in advance is beneficial for taking early action to avoid malicious attacks. In this study, we compose a colored Petri net model of Bitcoin. Our model consists of a given number of nodes, and each node has five subpages representing the node structure: proof of work, broadcast blocks, verify blocks, and the process of adding blocks to blockchain, respectively. Simulation results of fork probability can be easily obtained and analyzed by observing the data in the measuring components of subpages. The results show that our model correctly simulates the fork probability: on recent Bitcoin data, compared with the results of the wide-known SimBlock simulator, a difference of some 4.3% has been obtained. Thus, taking into account vivid graphical representation, our model has certain advantages for the developing techniques of attack avoidance.

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Publication Details

Published
2024-10-06
DOI
https://doi.org/10.1109/smc54092.2024.10831492
Primary Topic
Advanced Steganography and Watermarking Techniques
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article
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article

Analysis of Bitcoin Fork by Colored Petri Nets

Dmitry A. Zaitsev, Zeyu Zhou, Tatiana R. Shmeleva, Ding Liu
Advanced Steganography and Watermarking Techniques
article

Analysis of Bitcoin Fork by Colored Petri Nets

Dmitry A. Zaitsev, Zeyu Zhou, Tatiana R. Shmeleva, Ding Liu
article en

Abstract

Bitcoin is under the threat of fork since it operates with a distributed ledger. Predicting the fork probability in advance is beneficial for taking early action to avoid malicious attacks. In this study, we compose a colored Petri net model of Bitcoin. Our model consists of a given number of nodes, and each node has five subpages representing the node structure: proof of work, broadcast blocks, verify blocks, and the process of adding blocks to blockchain, respectively. Simulation results of fork probability can be easily obtained and analyzed by observing the data in the measuring components of subpages. The results show that our model correctly simulates the fork probability: on recent Bitcoin data, compared with the results of the wide-known SimBlock simulator, a difference of some 4.3% has been obtained. Thus, taking into account vivid graphical representation, our model has certain advantages for the developing techniques of attack avoidance.

Xidian University (CN), University of Derby (GB), Max Planck Institute for Software Systems (DE)
Zero hunger
Openalex Percentile: Top 74%
Advanced Steganography and Watermarking Techniques
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