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Cross-Layer Deanonymization Methods in the Lightning Protocol

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Financial Cryptography and Data Security (FC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12674))

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Abstract

Bitcoin (BTC) pseudonyms (layer 1) can effectively be deanonymized using heuristic clustering techniques. However, while performing transactions off-chain (layer 2) in the Lightning Network (LN) seems to enhance privacy, a systematic analysis of the anonymity and privacy leakages due to the interaction between the two layers is missing. We present (Please, find the full version of this paper with appendix at https://arxiv.org/abs/2007.00764.) clustering heuristics that group BTC addresses, based on their interaction with the LN, as well as LN nodes, based on shared naming and hosting information. We also present linking heuristics that link \(45.97\)% of all LN nodes to \(29.61\)% BTC addresses interacting with the LN. These links allow us to attribute information (e.g., aliases, IP addresses) to \(21.19\)% of the BTC addresses contributing to their deanonymization. Further, these deanonymization results suggest that the security and privacy of LN payments are weaker than commonly believed, with LN users being at the mercy of as few as five actors that control 36 nodes and over \(33\%\) of the total capacity. Overall, this is the first paper to present a method for linking LN nodes with BTC addresses across layers and to discuss privacy and security implications.

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Notes

  1. 1.

    The proprietary attribution data from Chainalysis is not included in the published dataset. The reader can contact the company for further inquiry.

  2. 2.

    Although theoretically a payment channel can be dual-funded (i.e., Bob also contributes \(x _1\) to the funding transaction), this feature is under discussion in the community [3] and currently only single-funded channels are implemented in practice.

  3. 3.

    https://api.graphsense.info/.

  4. 4.

    https://github.com/Blockstream/esplora/blob/master/API.md.

  5. 5.

    Some channels were opened with the same funding transaction.

  6. 6.

    https://github.com/nopara73/WasabiVsSamourai.

  7. 7.

    https://www.chainalysis.com/.

  8. 8.

    https://docs.wasabiwallet.io/using-wasabi.

  9. 9.

    We note that this requirement may no longer be there if the “fund-from-external-wallet” functionality, already available in the recent release [19], is widely adopted.

  10. 10.

    Here we do not consider source and destination entities as they do not directly interact with the LN.

  11. 11.

    We note that Chainalysis attribution data is not strictly necessary for the linking algorithms.

References

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  3. Community, L.N.: Wip: dual funding (v2 channel establishment protocol). Github Issue. https://github.com/lightningnetwork/lightning-rfc/pull/524

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Acknowledgments

This work is partially funded by the European Research Council (ERC) under the European Unions Horizon 2020 research (grant agreement No 771527-BROWSEC), by PROFET (grant agreement P31621), by the Austrian Research Promotion Agency through the Bridge-1 project PR4DLT (grant agreement 13808694); by COMET K1 SBA, ABC, by CoBloX Labs, by the Austrian Science Fund (FWF) through the Meitner program (project agreement M 2608-G27) and by the Austrian security research programme KIRAS of the Federal Ministry of Agriculture, Regions and Tourism (BMLRT) under the project KRYPTOMONITOR (879686). The authors would also like to thank Peter Holzer and Marcel Müller for setting up and starting the LN data collection process.

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Authors and Affiliations

  1. AIT - Austrian Institute of Technology, Vienna, Austria

    Matteo Romiti & Bernhard Haslhofer

  2. Technische Universität Berlin, Berlin, Germany

    Friedhelm Victor

  3. IMDEA Software Institute, Madrid, Spain

    Pedro Moreno-Sanchez

  4. Technische Universität Wien, Vienna, Austria

    Matteo Maffei

  5. Chainalysis, New York City, USA

    Peter Sebastian Nordholt

Authors
  1. Matteo Romiti
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  2. Friedhelm Victor
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  3. Pedro Moreno-Sanchez
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  4. Peter Sebastian Nordholt
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  5. Bernhard Haslhofer
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  6. Matteo Maffei
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Corresponding author

Correspondence to Matteo Romiti .

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Editors and Affiliations

  1. University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Nikita Borisov

  2. KU Leuven, Leuven, Belgium

    Claudia Diaz

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Romiti, M., Victor, F., Moreno-Sanchez, P., Nordholt, P.S., Haslhofer, B., Maffei, M. (2021). Cross-Layer Deanonymization Methods in the Lightning Protocol. In: Borisov, N., Diaz, C. (eds) Financial Cryptography and Data Security. FC 2021. Lecture Notes in Computer Science(), vol 12674. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-64322-8_9

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  • DOI: https://doi.org/10.1007/978-3-662-64322-8_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-64321-1

  • Online ISBN: 978-3-662-64322-8

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