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

中文翻译：

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分析和检测在线社交网络中的洗钱帐户

OSN中的虚拟货币在支持各种金融活动（例如货币兑换，在线购物和付费游戏）中扮演着越来越重要的角色。用户通常使用真实货币购买虚拟货币。这一事实促使攻击者利用一支帐户大军以不道德的或非法的方式不道德地或非法地收集虚拟货币，然后清洗收集的虚拟货币以获取巨额利润。此类攻击不仅给受害者用户造成巨大的经济损失，而且还损害了生态系统的生存能力。因此，检测参与清洗虚拟货币的恶意OSN帐户至关重要。为此，我们根据从全球最大的OSN之一腾讯QQ收集的操作数据，广泛研究了恶意帐户和良性帐户的行为。然后，我们设计了多方面的功能，这些功能从三个方面对帐户进行了特征描述：帐户生存能力，交易顺序以及帐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整合这些特征的检测方法，该方法可以实现94.2％的高检测率