XChainDataGen: A Cross-Chain Dataset Generation Framework
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866909540799217664 |
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| author | Augusto, André Vasconcelos, André Correia, Miguel Zhang, Luyao |
| author_facet | Augusto, André Vasconcelos, André Correia, Miguel Zhang, Luyao |
| contents | The number of blockchain interoperability protocols for transferring data and assets between blockchains has grown significantly. However, no open dataset of cross-chain transactions exists to study interoperability protocols in operation. There is also no tool to generate such datasets and make them available to the community. This paper proposes XChainDataGen, a tool to extract cross-chain data from blockchains and generate datasets of cross-chain transactions (cctxs). Using XChainDataGen, we extracted over 35 GB of data from five cross-chain protocols deployed on 11 blockchains in the last seven months of 2024, identifying 11,285,753 cctxs that moved over 28 billion USD in cross-chain token transfers. Using the data collected, we compare protocols and provide insights into their security, cost, and performance trade-offs. As examples, we highlight differences between protocols that require full finality on the source blockchain and those that only demand soft finality (\textit{security}). We compare user costs, fee models, and the impact of variables such as the Ethereum gas price on protocol fees (\textit{cost}). Finally, we produce the first analysis of the implications of EIP-7683 for cross-chain intents, which are increasingly popular and greatly improve the speed with which cctxs are processed (\textit{performance}), thereby enhancing the user experience. The availability of XChainDataGen and this dataset allows various analyses, including trends in cross-chain activity, security assessments of interoperability protocols, and financial research on decentralized finance (DeFi) protocols. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_13637 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | XChainDataGen: A Cross-Chain Dataset Generation Framework Augusto, André Vasconcelos, André Correia, Miguel Zhang, Luyao Cryptography and Security Distributed, Parallel, and Cluster Computing The number of blockchain interoperability protocols for transferring data and assets between blockchains has grown significantly. However, no open dataset of cross-chain transactions exists to study interoperability protocols in operation. There is also no tool to generate such datasets and make them available to the community. This paper proposes XChainDataGen, a tool to extract cross-chain data from blockchains and generate datasets of cross-chain transactions (cctxs). Using XChainDataGen, we extracted over 35 GB of data from five cross-chain protocols deployed on 11 blockchains in the last seven months of 2024, identifying 11,285,753 cctxs that moved over 28 billion USD in cross-chain token transfers. Using the data collected, we compare protocols and provide insights into their security, cost, and performance trade-offs. As examples, we highlight differences between protocols that require full finality on the source blockchain and those that only demand soft finality (\textit{security}). We compare user costs, fee models, and the impact of variables such as the Ethereum gas price on protocol fees (\textit{cost}). Finally, we produce the first analysis of the implications of EIP-7683 for cross-chain intents, which are increasingly popular and greatly improve the speed with which cctxs are processed (\textit{performance}), thereby enhancing the user experience. The availability of XChainDataGen and this dataset allows various analyses, including trends in cross-chain activity, security assessments of interoperability protocols, and financial research on decentralized finance (DeFi) protocols. |
| title | XChainDataGen: A Cross-Chain Dataset Generation Framework |
| topic | Cryptography and Security Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2503.13637 |