Dan Lin, Jiajing Wu, Yuxin Su, Ziye Zheng, Yuhong Nan, Zibin Zheng
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CONNECTOR: Enhancing the Traceability of Decentralized Bridge Applications via Automatic Cross-chain Transaction Association
Decentralized bridge applications are important software that connects
various blockchains and facilitates cross-chain asset transfer in the
decentralized finance (DeFi) ecosystem which currently operates in a
multi-chain environment. Cross-chain transaction association identifies and
matches unique transactions executed by bridge DApps, which is important
research to enhance the traceability of cross-chain bridge DApps. However,
existing methods rely entirely on unobservable internal ledgers or APIs,
violating the open and decentralized properties of blockchain. In this paper,
we analyze the challenges of this issue and then present CONNECTOR, an
automated cross-chain transaction association analysis method based on bridge
smart contracts. Specifically, CONNECTOR first identifies deposit transactions
by extracting distinctive and generic features from the transaction traces of
bridge contracts. With the accurate deposit transactions, CONNECTOR mines the
execution logs of bridge contracts to achieve withdrawal transaction matching.
We conduct real-world experiments on different types of bridges to demonstrate
the effectiveness of CONNECTOR. The experiment demonstrates that CONNECTOR
successfully identifies 100% deposit transactions, associates 95.81% withdrawal
transactions, and surpasses methods for CeFi bridges. Based on the association
results, we obtain interesting findings about cross-chain transaction behaviors
in DeFi bridges and analyze the tracing abilities of CONNECTOR to assist the
DeFi bridge apps.