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LineageChain: a fine-grained, secure and efficient data provenance system for blockchains

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Abstract

The success of Bitcoin and other cryptocurrencies is drawing significant interest to blockchains. A blockchain system implements a tamper-evident ledger for recording transactions that modify some global states. The system captures the entire evolution history of the states. The management of that history, also known as data provenance or lineage, has been studied extensively in database systems. However, querying data history in existing blockchains can only be done by replaying all transactions. This approach is applicable to large-scale, offline analysis, but is not suitable for online transaction processing. In this paper, we identify a new class of blockchain applications whose execution logics depend on provenance information at runtime. We first motivate the need for adding native provenance support to blockchains. We then present LineageChain, a fine-grained, secure and efficient provenance system for blockchains. LineageChain exposes lineage information to smart contracts runtime via simple and elegant interfaces that efficiently and securely support provenance-dependent contracts. LineageChain captures provenance during contract execution and stores it in a Merkle tree. LineageChain provides a novel skip list index designed for efficient provenance queries. We have implemented LineageChain on top of Fabric and a blockchain optimized storage system called ForkBase. Our extensive evaluation of LineageChain demonstrates its benefits to the new class of blockchain applications, its high query performance and its small storage overhead.

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Acknowledgements

This research is supported by Singapore Ministry of Education Academic Research Fund Tier 3 under MOE’s official grant number MOE2017-T3-1-007.

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Authors and Affiliations

  1. National University of Singapore, Singapore, Singapore

    Pingcheng Ruan, Qian Lin & Beng Chin Ooi

  2. Singapore University of Technology and Design, Singapore, Singapore

    Tien Tuan Anh Dinh

  3. Beijing Institute of Technology, Beijing, China

    Meihui Zhang

  4. Zhejiang University, Hangzhou, China

    Gang Chen

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  1. Pingcheng Ruan
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Correspondence to Pingcheng Ruan.

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Ruan, P., Dinh, T.T.A., Lin, Q. et al. LineageChain: a fine-grained, secure and efficient data provenance system for blockchains. The VLDB Journal 30, 3–24 (2021). https://doi.org/10.1007/s00778-020-00646-1

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