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FPPW: A Fair and Privacy Preserving Watchtower for Bitcoin

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Financial Cryptography and Data Security (FC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12675))

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Abstract

In this paper, we introduce FPPW, a new payment channel with watchtower scheme for Bitcoin. This new scheme provides fairness w.r.t. all channel participants including both channel parties and the watchtower. It means that the funds of any honest channel participant are safe even assuming that other two channel participants are corrupted and/or collude with each other. Furthermore, the watchtower in FPPW learns no information about the off-chain transactions and hence FPPW provides privacy against the watchtower. As a byproduct, we also define the coverage of a watchtower scheme, that is the total capacity of channels that a watchtower can cover on a scale of 0 to 1, and show that FPPW’s coverage is higher than those of PISA and Cerberus. The scheme can be implemented without any update in Bitcoin script.

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Notes

  1. 1.

    Due to lack of space, this will be presented in the technical report [15].

  2. 2.

    If in the defined privacy game, the channel setup for two channels could be different and the sequence \((\mathbf{x}_{\mathcal {P},[0,n]},\mathbf{x}_{\bar{\mathcal {P}},[0,n]})\) is given to the passive PPT adversarial watchtower, then the privacy guarantee is stronger. While Monitor, DCWC, and Outpost provide such stronger privacy guarantee, PISA provides weak privacy as defined in Definition 3 and Cerberus does not achieve privacy against watchtower.

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Acknowledgements

This research was partially supported by the Australian Government through the Australian Research Council’s Discovery Projects funding scheme (project DP180102199) and Discovery Early Career Award (project DE210100019).

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Correspondence to Arash Mirzaei .

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Mirzaei, A., Sakzad, A., Yu, J., Steinfeld, R. (2021). FPPW: A Fair and Privacy Preserving Watchtower for Bitcoin. In: Borisov, N., Diaz, C. (eds) Financial Cryptography and Data Security. FC 2021. Lecture Notes in Computer Science(), vol 12675. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-64331-0_8

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  • DOI: https://doi.org/10.1007/978-3-662-64331-0_8

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