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arXiv 2007.13639cs.CR
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不要浑水摸鱼!表征冠状病毒为主题的加密货币骗局

Don't Fish in Troubled Waters! Characterizing Coronavirus-themed Cryptocurrency Scams

Pengcheng Xia, Haoyu Wang, Xiapu Luo, Lei Wu, Yajin Zhou, Guangdong Bai, Guoai Xu, Gang Huang, Xuanzhe Liu

摘要:

随着COVID-19自二零二零年初开始在全球蔓延,越来越多的恶意活动正在利用COVID-19的话题。以COVID-19为主题的加密货币诈骗在疫情期间越来越受欢迎。然而,这些新出现的骗局对我们的社区知之甚少。在本文中,我们提出了COVID-19主题加密货币骗局的第一个测量研究。我们首先通过手动分析用户从在线资源报告的现有诈骗,创建COVID-19诈骗的全面分类。然后,我们提出了一种混合方法来执行调查:1)收集野生报告的诈骗; 2)根据从可疑实体收集的信息检测未公开的诈骗(例如,域、推文等)。我们总共收集了195个确认的COVID-19加密货币骗局,包括91个代币骗局,19个赠品骗局,9个勒索骗局,14个加密恶意软件骗局,9个庞氏骗局骗局和53个捐赠骗局。然后,我们确定了与这些骗局相关的200多个区块链地址,这些地址导致6,329名受害者损失至少33万美元。对于每种类型的骗局,我们进一步调查了他们使用的技巧和社会工程技术。为了方便未来的研究,我们已经向研究界发布了所有标记良好的骗局。

英文摘要:

As COVID-19 has been spreading across the world since early 2020, a growing number of malicious campaigns are capitalizing the topic of COVID-19. COVID-19 themed cryptocurrency scams are increasingly popular during the pandemic. However, these newly emerging scams are poorly understood by our community. In this paper, we present the first measurement study of COVID-19 themed cryptocurrency scams. We first create a comprehensive taxonomy of COVID-19 scams by manually analyzing the existing scams reported by users from online resources. Then, we propose a hybrid approach to perform the investigation by: 1) collecting reported scams in the wild; and 2) detecting undisclosed ones based on information collected from suspicious entities (e.g., domains, tweets, etc). We have collected 195 confirmed COVID-19 cryptocurrency scams in total, including 91 token scams, 19 giveaway scams, 9 blackmail scams, 14 crypto malware scams, 9 Ponzi scheme scams, and 53 donation scams. We then identified over 200 blockchain addresses associated with these scams, which lead to at least 330K US dollars in losses from 6,329 victims. For each type of scams, we further investigated the tricks and social engineering techniques they used. To facilitate future research, we have released all the well-labelled scams to the research community.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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