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Turbo: A High-Performance and Secure Off-Chain Payment Hub

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Machine Learning for Cyber Security (ML4CS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13657))

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Abstract

The scalability problems of blockchain systems are drastically amplified with the emergence of large-scale instantaneous transaction scenarios. Off-chain protocols are a prominent approach to alleviate these challenges. Payment channels allow two parties to lock funds inside the payment channel to enable instant transactions without involving the blockchain. The latest proposed payment hub (PH) allows off-chain transactions between multi-party through a tumbler. However, existing PH suffers from the problem of centralization, low throughput, and expensive challenge processes. We present Turbo, which allows direct, fast, and low-cost off-chain transactions between muti-party. Turbo allows any party to initiate arbitration against the guilty leader via the Immediate Fraud Proof Challenge (IFPC). Compared to NOCUST, Turbo increases throughput by approximately 30x and decreases the cost of the challenge by 50%. Moreover, Turbo reduces the complexity of the challenge process to O (1).

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Acknowledgment

This work was funded by grants from the National Key Research and Development Program of China (Grant No. 2021YFB2700300).

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Authors and Affiliations

  1. Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, China

    Jinchun He, Rixin He, Shengda Zhuo & Wanqing Jie

  2. Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing, China

    Wangjie Qiu

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  1. Jinchun He
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  2. Wangjie Qiu
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  3. Rixin He
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  4. Shengda Zhuo
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  5. Wanqing Jie
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Corresponding author

Correspondence to Wangjie Qiu .

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Editors and Affiliations

  1. School of Computing and Informatics, University of Louisiana at Lafayette, Lafayette, IN, USA

    Yuan Xu

  2. Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, China

    Hongyang Yan

  3. Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, China

    Huang Teng

  4. Guangdong Polytechnic Normal University, Guangzhou, China

    Jun Cai

  5. Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, China

    Jin Li

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He, J., Qiu, W., He, R., Zhuo, S., Jie, W. (2023). Turbo: A High-Performance and Secure Off-Chain Payment Hub. In: Xu, Y., Yan, H., Teng, H., Cai, J., Li, J. (eds) Machine Learning for Cyber Security. ML4CS 2022. Lecture Notes in Computer Science, vol 13657. Springer, Cham. https://doi.org/10.1007/978-3-031-20102-8_6

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  • DOI: https://doi.org/10.1007/978-3-031-20102-8_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-20101-1

  • Online ISBN: 978-3-031-20102-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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