Modern fraudsters write malicious programs to coordinate a group of accounts to commit collective fraud for illegal profits in online platforms. These programs have access to a set of finite resources - a set of IPs, devices, and accounts etc. and sometime manipulate fake accounts to collaboratively attack the target system. Inspired by these observations, we share our experience in building two real-time risk control systems to detect collective fraud. We show that with TigerGraph, a powerful graph database, and its innovative query language - GSQL, data scientists and fraud experts can conveniently implement and deploy an end-to-end risk control system as a graph database application.

中文翻译：

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连接点以打击集体欺诈

现代欺诈者编写恶意程序来协调一组帐户，以在网上平台中为非法利润进行集体欺诈。这些程序可以访问一组有限的资源-一组IP，设备和帐户等，并且有时可以操纵伪造的帐户来协同攻击目标系统。受这些观察的启发，我们分享了构建两个实时风险控制系统以检测集体欺诈的经验。我们证明，借助功能强大的图形数据库TigerGraph及其创新的查询语言-GSQL，数据科学家和欺诈专家可以方便地实现和部署端到端风险控制系统作为图形数据库应用程序。