@inproceedings{c639664615e145ef92fe09cfaa8330b2,
title = "Transaction Deanonymization in Large-Scale Bitcoin Systems via Propagation Pattern Analysis",
abstract = "Bitcoin is a digital currency payment system, which bases on the property of decentralization and anonymization of Blockchain. Researches on transaction deanonymization for the Bitcoin system may not associate anonymous transactions with the IP addresses (physical identity) of the originator accurately and may consume network resources excessively. In this paper, we propose an approach to obtain the originating transactions through analyzing the propagation information. We calculate a pattern matching score by combining the propagation pattern extraction and the node weight assignment. Through carrying out the experiments in the real Bitcoin system, we effectively match the originating transactions with the target node, which reaches a precision of 81.3% and is 30% higher than the state-of-the-art method.",
keywords = "Bitcoin transactions, Data analytics, Deanonymization, Empirical probability distribution, Propagation path",
author = "Meng Shen and Junxian Duan and Ning Shang and Liehuang Zhu",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Singapore Pte Ltd.; 1st International Conference on Security and Privacy in Digital Economy, SPDE 2020 ; Conference date: 30-10-2020 Through 01-11-2020",
year = "2020",
doi = "10.1007/978-981-15-9129-7_45",
language = "English",
isbn = "9789811591280",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "661--675",
editor = "Shui Yu and Peter Mueller and Jiangbo Qian",
booktitle = "Security and Privacy in Digital Economy - 1st International Conference, SPDE 2020, Proceedings",
address = "Germany",
}