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Double-Layer Blockchain-Based Decentralized Integrity Verification for Multi-chain Cross-Chain Data

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Neural Information Processing (ICONIP 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14452))

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Abstract

With the development of blockchain technology, issues like storage, throughput, and latency emerge. Multi-chain solutions are devised to enable data sharing across blockchains, but in complex cross-chain scenarios, data integrity faces risks. Due to the decentralized nature of blockchain, centralized verification schemes are not feasible, making decentralized cross-chain data integrity verification a critical and challenging problem. In this paper, based on the ideas of “governing the chain by chain” and “double layer blockchain”, we propose a double-layer blockchain-based decentralized integrity verification scheme. We construct a supervision-chain by selecting representative nodes from multiple blockchains, which is responsible for cross-chain data integrity verification and recording results. Specifically, our scheme relies on two consensus phases: integrity consensus for verification and block consensus for result recording. We also integrate a reputation system and an election algorithm within the supervision-chain. Through security analysis and performance evaluation, we demonstrate the security and effectiveness of our proposed scheme.

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Acknowledgement

This work is supported by the Fundamental Research Funds for the Central Universities (Grant No. NS2023047), the National Key Research and Development Program of China (Grant No. 2020YFB1005500) and Postgraduate Research & Practice Innovation Program of NUAA (No. xcxjh20221616).

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Correspondence to Yuqian Zhou or Dan Li .

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Wei, W., Zhou, Y., Li, D., Hong, X. (2024). Double-Layer Blockchain-Based Decentralized Integrity Verification for Multi-chain Cross-Chain Data. In: Luo, B., Cheng, L., Wu, ZG., Li, H., Li, C. (eds) Neural Information Processing. ICONIP 2023. Lecture Notes in Computer Science, vol 14452. Springer, Singapore. https://doi.org/10.1007/978-981-99-8076-5_19

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  • DOI: https://doi.org/10.1007/978-981-99-8076-5_19

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-8075-8

  • Online ISBN: 978-981-99-8076-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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