Using Web-Scale Graph Analytics to Counter Technical Support Scams - Larson, Jonathan; Tower, Bryan; Hadfield, Duane; Edge, Darren; White, Chris (GTA³ 2.0: The 2nd IEEE Big Data Workshop on Graph Techniques for Adversarial Activity Analytics, 2018)
Technical Support Scams delivered through malicious webpages and linked advertisements are an endemic problem on the web. To avoid detection, scammers systematically vary the URLs, web page designs, and phone numbers of scam delivery. We describe a web-scale pipeline powered by Cloud AI services that continuously detects and links evidence of such scams. By integrating this evidence in a graph structure and exposing it for forensic analysis in a user interface, we enable investigators and law enforcement partners to track the evolving scope and sophistication of scam operations. This approach automates and scales investigative tradecraft that contributed to major enforcement actions by the FTC in 2016. From 2016-2018, it helped reduce consumer exposure to such scams by 5 percent.