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RecAGT: Shard Testable Codes with Adaptive Group Testing for Malicious Nodes Identification in Sharding Permissioned Blockchain

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Algorithms and Architectures for Parallel Processing (ICA3PP 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14490))

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Abstract

Recently, permissioned blockchain has been extensively explored in various fields, such as asset management, supply chain, healthcare, and many others. Many scholars are dedicated to improving its verifiability, scalability, and performance based on sharding techniques, including grouping nodes and handling cross-shard transactions. However, they ignore the node vulnerability problem, i.e., there is no guarantee that nodes will not be maliciously controlled throughout their life cycle. Facing this challenge, we propose RecAGT, a novel identification scheme aimed at reducing communication overhead and identifying potential malicious nodes. First, shard testable codes are designed to encode the original data in case of a leak of confidential data. Second, a new identity proof protocol is presented as evidence against malicious behavior. Finally, adaptive group testing is chosen to identify malicious nodes. Notably, our work focuses on the internal operation within the committee and can thus be applied to any sharding permissioned blockchains. Simulation results show that our proposed scheme can effectively identify malicious nodes with low communication and computational costs.

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Notes

  1. 1.

    Honest nodes are those that perform normally following the rules of the system (e.g., read, write or maintain blocks and perform or relay transactions).

  2. 2.

    The behaviors of malicious (or Byzantine) nodes could censor, reverse, reorder or withhold specific transactions without including them in any block to interfere with the system [13].

  3. 3.

    Generally speaking, permissioned blockchains can be divided into private and consortium blockchains since both of them only allow nodes with identity to join the network. Our study primarily focuses on consortium blockchains due to their alignment with the idea of decentralization.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (62072321, 61972272), the Six Talent Peak Project of Jiangsu Province (XYDXX-084), the China Postdoctoral Science Foundation (2020M671597), the Jiangsu Postdoctoral Research Foundation (2020Z100), Suzhou Planning Project of Science and Technology (SS202023), the Future Network Scientific Research Fund Project (FNSRFP-2021-YB-38), Natural Science Foundation of the Higher Education Institutions of Jiangsu Province (22KJA520007, 20KJB520002), the Collaborative Innovation Center of Novel Software Technology and Industrialization, and Soochow University Interdisciplinary Research Project for Young Scholars in the Humanities.

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Authors and Affiliations

  1. School of Computer Science and Technology, Soochow University, Suzhou, China

    Dongyang Yu, Jin Wang, Lingzhi Li, Wei Jiang & Can Liu

  2. School of Future Science and Engineering, Soochow University, Suzhou, China

    Jin Wang

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  1. Dongyang Yu
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  2. Jin Wang
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  3. Lingzhi Li
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  4. Wei Jiang
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  5. Can Liu
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Corresponding authors

Correspondence to Jin Wang or Lingzhi Li .

Editor information

Editors and Affiliations

  1. Royal Melbourne Institute of Technology, Melbourne, VIC, Australia

    Zahir Tari

  2. Tianjin University, Tianjin, China

    Keqiu Li

  3. University of Arizona, Tucson, AZ, USA

    Hongyi Wu

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Yu, D., Wang, J., Li, L., Jiang, W., Liu, C. (2024). RecAGT: Shard Testable Codes with Adaptive Group Testing for Malicious Nodes Identification in Sharding Permissioned Blockchain. In: Tari, Z., Li, K., Wu, H. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2023. Lecture Notes in Computer Science, vol 14490. Springer, Singapore. https://doi.org/10.1007/978-981-97-0859-8_24

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  • DOI: https://doi.org/10.1007/978-981-97-0859-8_24

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-0858-1

  • Online ISBN: 978-981-97-0859-8

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