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An Empirical Analysis of Privacy in the Lightning Network

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arxiv 2003.12470 v3 pith:QDDLEZEN submitted 2020-03-27 cs.CR

classification cs.CR
keywords networklightningprivacyanalysisavailableinformationofferedpayment
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Payment channel networks, and the Lightning Network in particular, seem to offer a solution to the lack of scalability and privacy offered by Bitcoin and other blockchain-based cryptocurrencies. Previous research has focused on the scalability, availability, and crypto-economics of the Lightning Network, but relatively little attention has been paid to exploring the level of privacy it achieves in practice. This paper presents a thorough analysis of the privacy offered by the Lightning Network, by presenting several attacks that exploit publicly available information about the network in order to learn information that is designed to be kept secret, such as how many coins a node has available or who the sender and recipient are in a payment routed through the network.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Matrices over a Hilbert space and their low-rank cross approximation

    math.NA 2025-05 conditional novelty 5.0 of 10

    Bochner matrices (matrices with Hilbert-space entries) admit cross decompositions and a new adaptive cross-dyadic approximation algorithm that numerically approximates parametric PDE solution maps.

  2. Color Image Set Recognition Based on Quaternionic Grassmannians

    cs.CV 2025-05 reject novelty 4.0 of 10

    Color image sets are mapped to quaternionic subspaces and classified by a proposed geodesic distance formula, tested on ETH-80 and highway traffic videos.

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