Cross-Layer Deanonymization Methods in the Lightning Protocol
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Dionysis Zindros
Feb 9, 2021, 8:30:03 AM2/9/21
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Tomorrow, Wednesday, February 10, 2021, 04:00 PM UTC, Romiti Matteo and Friedhelm Victor from the Austrian Institute of Technology and Technische Universität Berlin will present "Cross-Layer Deanonymization Methods in the Lightning Protocol".
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 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.
Join here: https://zoom.us/j/98734915337?pwd=UmNNQmNyVmUvT2c3dHZ6UjgrUnhhZz09
Password: D9ES29
More seminars: https://decrypto.org/seminar
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 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.
Join here: https://zoom.us/j/98734915337?pwd=UmNNQmNyVmUvT2c3dHZ6UjgrUnhhZz09
Password: D9ES29
More seminars: https://decrypto.org/seminar
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