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Hide & Seek: Privacy-Preserving Rebalancing on Payment Channel Networks

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Financial Cryptography and Data Security (FC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13411))

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Abstract

Payment channels effectively move the transaction load off-chain thereby successfully addressing the inherent scalability problem most cryptocurrencies face. A major drawback of payment channels is the need to “top up” funds on-chain when a channel is depleted. Rebalancing was proposed to alleviate this issue, where parties with depleting channels move their funds along a cycle to replenish their channels off-chain. Protocols for rebalancing so far either introduce local solutions or compromise privacy.

In this work, we present an opt-in rebalancing protocol that is both private and globally optimal, meaning our protocol maximizes the total amount of rebalanced funds. We study rebalancing from the framework of linear programming. To obtain full privacy guarantees, we leverage multi-party computation in solving the linear program, which is executed by selected participants to maintain efficiency. Finally, we efficiently decompose the rebalancing solution into incentive-compatible cycles which conserve user balances when executed atomically.

Supported by the Vienna Cybersecurity and Privacy Research Center (ViSP), funded by the Vienna business agency (Wirtschaftsagentur), 2020–2023.

Supported partially by the Austrian Science Fund (FWF) project “Design Framework for Self-Driving Networks” (ADVISE), I 4800-N, 2020–2023 and Vienna Cybersecurity and Privacy Research Center (ViSP), funded by the Vienna business agency (Wirtschaftsagentur), 2020–2023.

Supported partially by ERC Starting Grant QIP–805241, the Vienna Cybersecurity and Privacy Research Center (ViSP), funded by the Vienna business agency (Wirtschaftsagentur), 2020–2023, and by Harmony through the Research DAO.

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Author information

Authors and Affiliations

  1. IST Austria, Klosterneuburg, Austria

    Zeta Avarikioti, Krzysztof Pietrzak & Michelle Yeo

  2. Faculty of Computer Science, University of Vienna, Wien, Austria

    Iosif Salem & Stefan Schmid

  3. Centrum Wiskunde & Informatica, Amsterdam, The Netherlands

    Samarth Tiwari

Authors
  1. Zeta Avarikioti
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  2. Krzysztof Pietrzak
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  3. Iosif Salem
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  4. Stefan Schmid
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  5. Samarth Tiwari
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  6. Michelle Yeo
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Corresponding author

Correspondence to Samarth Tiwari .

Editor information

Editors and Affiliations

  1. Technion - Israel Institute of Technology, Haifa, Israel

    Ittay Eyal

  2. Texas A&M University, College Station, TX, USA

    Juan Garay

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© 2022 International Financial Cryptography Association

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Avarikioti, Z., Pietrzak, K., Salem, I., Schmid, S., Tiwari, S., Yeo, M. (2022). Hide & Seek: Privacy-Preserving Rebalancing on Payment Channel Networks. In: Eyal, I., Garay, J. (eds) Financial Cryptography and Data Security. FC 2022. Lecture Notes in Computer Science, vol 13411. Springer, Cham. https://doi.org/10.1007/978-3-031-18283-9_17

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  • DOI: https://doi.org/10.1007/978-3-031-18283-9_17

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