XSema: A Novel Framework for Semantic Extraction of Cross-chain Transactions

As the number of blockchain platforms continues to grow, the independence of these networks poses challenges for transferring assets and information across chains. Cross-chain bridge technology has emerged to address this issue, establishing communication protocols to facilitate cross-chain interaction of assets and information, thereby enhancing user experience. However, the complexity of cross-chain transactions increases the difficulty of security regulation, rendering traditional single-chain detection methods inadequate for cross-chain scenarios. Therefore, understanding cross-chain transaction semantics is crucial, as it forms the foundation for cross-chain security detection tasks. Although there are existing methods for extracting transaction semantics specifically for single chains, these approaches often overlook the unique characteristics of cross-chain scenarios, limiting their applicability. This paper introduces XSema, a novel cross-chain semantic extraction framework grounded in asset transfer and message-passing, designed specifically for cross-chain contexts. Experimental results demonstrate that XSema effectively distinguishes between cross-chain and non-cross-chain transactions, surpassing existing methods by over 9% for the generality metric and over 10% for the generalization metric. Furthermore, we analyze the underlying asset transfer patterns and message-passing event logs associated with cross-chain transactions. We offer new insights into the coexistence of multiple blockchains and the cross-chain ecosystem.

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Publication Details

Published
2024-12-13
DOI
https://doi.org/10.1109/hpcc64274.2024.00094
Citations
1
Primary Topic
Service-Oriented Architecture and Web Services
Type
article
Field-Weighted Citation Impact
0.78

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article

XSema: A Novel Framework for Semantic Extraction of Cross-chain Transactions

Ziye Zheng, Quanzhong Li, Jiajing Wu, Na Ruan et al.
1 citations
Service-Oriented Architecture and Web Services
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article

XSema: A Novel Framework for Semantic Extraction of Cross-chain Transactions

Ziye Zheng, Quanzhong Li, Jiajing Wu, Na Ruan, Dan Lin
article en
1 citations

Abstract

As the number of blockchain platforms continues to grow, the independence of these networks poses challenges for transferring assets and information across chains. Cross-chain bridge technology has emerged to address this issue, establishing communication protocols to facilitate cross-chain interaction of assets and information, thereby enhancing user experience. However, the complexity of cross-chain transactions increases the difficulty of security regulation, rendering traditional single-chain detection methods inadequate for cross-chain scenarios. Therefore, understanding cross-chain transaction semantics is crucial, as it forms the foundation for cross-chain security detection tasks. Although there are existing methods for extracting transaction semantics specifically for single chains, these approaches often overlook the unique characteristics of cross-chain scenarios, limiting their applicability. This paper introduces XSema, a novel cross-chain semantic extraction framework grounded in asset transfer and message-passing, designed specifically for cross-chain contexts. Experimental results demonstrate that XSema effectively distinguishes between cross-chain and non-cross-chain transactions, surpassing existing methods by over 9% for the generality metric and over 10% for the generalization metric. Furthermore, we analyze the underlying asset transfer patterns and message-passing event logs associated with cross-chain transactions. We offer new insights into the coexistence of multiple blockchains and the cross-chain ecosystem.

Sun Yat-sen University (CN), Shanghai Jiao Tong University (CN)
National Natural Science Foundation of China, Sun Yat-sen University, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 16%
Service-Oriented Architecture and Web Services
0.78
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