Buy Crypto, Sell Privacy: An Extended Investigation of the Cryptocurrency Exchange Evonax

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Alexander Brechlin, Jochen Schäfer, Frederik Armknecht
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Abstract

Cryptocurrency exchanges have become a multi-billion dollar industry. Although these platforms are not only relevant for economic reasons but also from a privacy and legal perspective, empirical studies investigating the operations of cryptocurrency exchanges and the behavior of their users are surprisingly rare. A notable exception is a study analyzing the cryptocurrency exchange ShapeShift. While this study described new heuristics to retrieve a significant fraction of trades made on the plaform, its approach relied on identifying cryptocurrency transactions based on previously scraped trade data. This limited the analysis to the timeframe for which data had been acquired and likely led to false negatives in the transaction identification process. In this paper, we replicate and extend previous work by conducting an in-depth investigation of the cryptocurrency exchange Evonax. Our analysis is based on actual trading data acquired by using a novel methodology allowing to extract detailed information from the public blockchain and the interface of the exchange platform. We are able to identify 30,402 transactions between the launch of Evonax in February 2018 and December 31, 2022, which should be close to a complete set of all transactions. This allows us not only to analyze the business practices of a cryptocurrency exchange but also to identify a number of interesting use cases that are likely to be associated with illegal activity. This paper is an extended version of a research article previously accepted at the CryptoEx Workshop at IEEE ICBC 2024.

Abstract Image

购买加密货币,出售隐私:对加密货币交易所Evonax的扩展调查
加密货币交易所已经成为一个价值数十亿美元的产业。尽管这些平台不仅与经济原因相关,而且从隐私和法律的角度来看也是相关的,但调查加密货币交易所的运营及其用户行为的实证研究却非常罕见。一个值得注意的例外是一项分析加密货币交易所shapesshift的研究。虽然这项研究描述了新的启发式方法来检索平台上进行的大部分交易,但其方法依赖于根据先前抓取的交易数据识别加密货币交易。这将分析限制在已获得数据的时间范围内,并可能导致交易识别过程中的错误否定。在本文中,我们通过对加密货币交易所Evonax进行深入调查来复制和扩展先前的工作。我们的分析是基于实际交易数据,通过使用一种新颖的方法,允许从公共区块链和交易平台的界面中提取详细信息。我们能够确定在2018年2月Evonax推出至2022年12月31日之间的30,402笔交易,这应该接近于所有交易的完整集合。这使我们不仅可以分析加密货币交易所的业务实践,还可以识别一些可能与非法活动相关的有趣用例。本文是先前在IEEE ICBC 2024的CryptoEx研讨会上接受的一篇研究文章的扩展版本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Network Management
International Journal of Network Management COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS
CiteScore
5.10
自引率
6.70%
发文量
25
审稿时长
>12 weeks
期刊介绍: Modern computer networks and communication systems are increasing in size, scope, and heterogeneity. The promise of a single end-to-end technology has not been realized and likely never will occur. The decreasing cost of bandwidth is increasing the possible applications of computer networks and communication systems to entirely new domains. Problems in integrating heterogeneous wired and wireless technologies, ensuring security and quality of service, and reliably operating large-scale systems including the inclusion of cloud computing have all emerged as important topics. The one constant is the need for network management. Challenges in network management have never been greater than they are today. The International Journal of Network Management is the forum for researchers, developers, and practitioners in network management to present their work to an international audience. The journal is dedicated to the dissemination of information, which will enable improved management, operation, and maintenance of computer networks and communication systems. The journal is peer reviewed and publishes original papers (both theoretical and experimental) by leading researchers, practitioners, and consultants from universities, research laboratories, and companies around the world. Issues with thematic or guest-edited special topics typically occur several times per year. Topic areas for the journal are largely defined by the taxonomy for network and service management developed by IFIP WG6.6, together with IEEE-CNOM, the IRTF-NMRG and the Emanics Network of Excellence.
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