Abstract
In recent years, blockchain has been widely used as a decentralized database. However, its limited scalability makes it unsuitable for large-scale applications. To overcome this challenge, high scalability cross-chain technologies have become crucial for implementing blockchain applications. While existing cross-chain technologies focus on implementing cross-chain logic, ignoring the issue of incomplete results that may arise when querying data provenance in cross-chain systems. In this work, we propose a cross-chain system that supports efficient and verifiable complete data provenance queries. We achieve this by designing an index based on a linear list and adjacent linked list to store related transactions, enabling us to perform a complete query. We also utilize vector commitments to generate verification objects indicating whether transactions are included in our index entries, ensuring verifiable integrity of query results. Furthermore, we construct an index structure based on B+ tree and Merkle tree to enhance the system’s availability and query efficiency. Our experimental results demonstrate that our scheme not only has excellent performance in terms of the cost of verification object, but it also improves query efficiency by approximately two times.
J. Tian and E. Zhou—These authors contributed equally to this work.
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Acknowledgement
This work is supported by the National Key Research and Development Program of China under Grant 2022YFB3102700, the National Natural Science Foundation of China under Grant 62132013, 62102295, 62202358, the Key Research and Development Programs of Shaanxi under Grants 2021ZDLGY06-03, the Guangdong Leading Talent Program No. 2016LJ06D658 and the Guangdong Innovation Team Program No. 2018KCXTD030. We also appreciate Alibaba Cloud Intelligent Computing LINGJUN to provide the powerful computation ability in the experiments.
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Tian, J., Xiao, Y., Zhou, E., Pei, Q. (2024). A Cross-Chain System Supports Verifiable Complete Data Provenance Queries. In: Tari, Z., Li, K., Wu, H. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2023. Lecture Notes in Computer Science, vol 14489. Springer, Singapore. https://doi.org/10.1007/978-981-97-0798-0_14
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