Reference : Transaction Clustering Using Network Traffic Analysis for Bitcoin and Derived Blockchains
Scientific congresses, symposiums and conference proceedings : Paper published in a journal
Engineering, computing & technology : Computer science
Security, Reliability and Trust
http://hdl.handle.net/10993/39728
Transaction Clustering Using Network Traffic Analysis for Bitcoin and Derived Blockchains
English
Biryukov, Alex mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) > ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)]
Tikhomirov, Sergei mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC) >]
2019
IEEE INFOCOM 2019 Workshop Proceedings
Yes
International
2nd Workshop on Cryptocurrencies and Blockchains for Distributed Systems (CryBlock) at IEEE INFOCOM 2019
29-04-2019
Paris
France
[en] bitcoin ; blockchain ; cryptocurrency ; privacy ; anonymity
[en] Bitcoin is a decentralized digital currency introduced in 2008 and launched in 2009. Bitcoin provides a way to transact without any trusted intermediary, but its privacy guarantees are questionable, and multiple deanonymization attacks have been proposed. Cryptocurrency privacy research has been mostly focused on blockchain analysis, i.e., extracting information from the transaction graph. We focus on another vector for privacy attacks: network analysis.

We describe the message propagation mechanics in Bitcoin and propose a novel technique for transaction clustering based on network traffic analysis. We show that timings of transaction messages leak information about their origin, which can be exploited by a well connected adversarial node. We implement and evaluate our method in the Bitcoin testnet with a high level of accuracy, deanonymizing our own transactions issued from a desktop wallet (Bitcoin Core) and from a mobile (Mycelium) wallet. Compared to existing approaches, we leverage the propagation information from multiple peers, which allows us to overcome an anti-deanonymization technique (“diffusion”) used in Bitcoin.
http://hdl.handle.net/10993/39728

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