Paper 2021/1401

HIDE & SEEK: Privacy-Preserving Rebalancing on Payment Channel Networks

Zeta Avarikioti, Krzysztof Pietrzak, Iosif Salem, Stefan Schmid, Samarth Tiwari, and Michelle Yeo


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.

Available format(s)
Publication info
Preprint. MINOR revision.
Payment Channel NetworksPrivacyand Rebalancing.
Contact author(s)
samarth tiwari @ cwi nl
2021-10-18: received
Short URL
Creative Commons Attribution


      author = {Zeta Avarikioti and Krzysztof Pietrzak and Iosif Salem and Stefan Schmid and Samarth Tiwari and Michelle Yeo},
      title = {{HIDE} & {SEEK}: Privacy-Preserving Rebalancing on Payment Channel Networks},
      howpublished = {Cryptology ePrint Archive, Paper 2021/1401},
      year = {2021},
      note = {\url{}},
      url = {}
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