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账户


OSN中的虚拟货币在支持货币兑换、在线购物、付费游戏等各种金融活动方面发挥着越来越重要的作用。用户通常使用真实货币购买虚拟货币。这一事实促使攻击者利用大量账户来以不道德或非法的方式以无成本或极低的成本收集虚拟货币，然后对收集到的虚拟货币进行洗钱以获取巨额利润。此类攻击不仅会给受害用户造成重大经济损失，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 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，广泛研究恶意和良性帐户的行为。然后，我们设计了多方面的特征，从三个方面来表征账户：账户生存能力、交易序列和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整合这些特征的检测方法，可以实现 94.2% 的高检测率