Analyzing and Detecting Money-Laundering Accounts in Online Social Networks
Analyzing and Detecting Money-Laundering Accounts in Online Social Networks
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分析和检测在线社交网络中的洗钱账户
DOI：
10.1109/mnet.2017.1700213
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发表时间：
2018-05
期刊：
影响因子：
9.3
通讯作者：
Jin Hongbo
中科院分区：
文献类型：
--
作者：
Zhou Yadong;Wang Ximi;Zhang Junjie;Zhang Peng;Liu Lili;Jin Huan;Jin Hongbo
OSN中的虚拟货币在支持货币兑换、在线购物和付费游戏等各种金融活动方面发挥着越来越重要的作用。用户通常使用真实的货币购买虚拟货币。这一事实促使攻击者利用大量账户以不道德或非法的方式收集虚拟货币，并且没有或非常低的成本，然后清洗收集的虚拟货币以获得巨额利润。这种攻击不仅会给受害用户带来巨大的经济损失，还会损害生态系统的生存能力。因此，检测参与洗钱虚拟货币的恶意OSN账户至关重要。为此，我们广泛研究了恶意和良性帐户的行为的基础上，从腾讯QQ，在世界上最大的OSN之一收集的操作数据。然后，我们设计了多方面的特征，从三个方面来描述账户：账户的生存能力，交易序列，账户之间的空间相关性。最后，我们提出了一种使用统计分类器综合这些特征的检测方法，该方法可以达到94.2%的高检测率。
Virtual currency in OSNs plays an increasingly important role in supporting various financial activities such as currency exchange, online shopping, and paid games. Users usually purchase virtual currency using real currency. This fact motivates attackers to instrument an army of accounts to collect virtual currency unethically or illegally with no or very low cost and then launder the collected virtual money for massive profit. Such attacks not only introduce significant financial loss of victim users, but also harm the viability of the ecosystem. It is therefore of central importance to detect malicious OSN accounts that engage in laundering virtual currency. To this end, we extensively study the behavior of both malicious and benign accounts based on operation data collected from Tencent QQ, one of the largest OSNs in the world. Then, we devise multi-faceted features that characterize accounts from three aspects: account viability, transaction sequences, and spatial correlation among accounts. Finally, we propose a detection method by integrating these features using a statistical classifier, which can achieve a high detection rate of 94.2 percen
影响因子：
5
作者：
Fu, Hao;Xie, Xing;Chen, Enhong
通讯作者：
Chen, Enhong