A Large-scale Empirical Analysis of Ransomware Activities in Bitcoin

被引:8
|
作者
Wang, Kai [1 ]
Pang, Jun [2 ]
Chen, Dingjie [3 ]
Zhao, Yu [3 ]
Huang, Dapeng [1 ]
Chen, Chen [3 ]
Han, Weili [3 ]
机构
[1] Fudan Univ, Sch Comp Sci, 2005 Songhu Rd, Shanghai 200438, Peoples R China
[2] Univ Luxembourg, Dept Comp Sci, 6 Ave Fonte, L-4364 Esch Sur Alzette, Luxembourg
[3] Fudan Univ, Software Sch, 2005 Songhu Rd, Shanghai 200438, Peoples R China
基金
国家重点研发计划; 中国博士后科学基金;
关键词
Bitcoin transactions; clustering; ransomware; VICTIMIZATION; OVERLAP;
D O I
10.1145/3494557
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Exploiting the anonymous mechanism of Bitcoin, ransomware activities demanding ransom in bitcoins have become rampant in recent years. Several existing studies quantify the impact of ransomware activities, mostly focusing on the amount of ransom. However, victims' reactions in Bitcoin that can well reflect the impact of ransomware activities are somehow largely neglected. Besides, existing studies track ransom transfers at the Bitcoin address level, making it difficult for them to uncover the patterns of ransom transfers from a macro perspective beyond Bitcoin addresses. In this article, we conduct a large-scale analysis of ransom payments, ransom transfers, and victim migrations in Bitcoin from 2012 to 2021. First, we develop a fine-grained address clustering method to cluster Bitcoin addresses into users, which enables us to identify more addresses controlled by ransomware criminals. Second, motivated by the fact that Bitcoin activities and their participants already formed stable industries, such as Darknet and Miner, we train a multi-label classification model to identify the industry identifiers of users. Third, we identify ransom payment transactions and then quantify the amount of ransom and the number of victims in 63 ransomware activities. Finally, after we analyze the trajectories of ransom transferred across different industries and track victims' migrations across industries, we find out that to obscure the purposes of their transfer trajectories, most ransomware criminals (e.g., operators of Locky and Wannacry) prefer to spread ransom into multiple industries instead of utilizing the services of Bitcoin mixers. Compared with other industries, Investment is highly resilient to ransomware activities in the sense that the number of users in Investment remains relatively stable. Moreover, we also observe that a few victims become active in the Darknet after paying ransom. Our findings in this work can help authorities deeply understand ransomware activities in Bitcoin. While our study focuses on ransomware, our methods are potentially applicable to other cybercriminal activities that have similarly adopted bitcoins as their payments.
引用
收藏
页数:29
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