Ctrl+Alt+Deceive: Quantifying User Exposure to Online Scams
Platon Kotzias, Michalis Pachilakis, Javier Aldana-Iuit, Juan Caballero, Iskander Sánchez-Rola, Leyla Bilge
Abstract
—Online scams have become a top threat for Internet users, inflicting $10 billion in losses in 2023 only in the US. Prior work has studied specific scam types, but no work has compared different scam types. In this work, we perform what we believe is the first study of the exposure of end users to different types of online scams. We examine seven popular scam types: shopping, financial, cryptocurrency, gambling, dating, funds recovery, and employment scams. To quantify end-user exposure, we search for observations of 607K scam domains over a period of several months by millions of desktop and mobile devices belonging to customers of a large cybersecurity vendor. We classify the scam domains into the seven scam types and measure for each scam type the exposure of end users, geographical variations, scam domain lifetime, and the promotion of scam websites through online advertisements. We examine 25.1M IP addresses accessing over 414K scam domains. On a daily basis, 149K devices are exposed to online scams, with an average of 101K (0.8%) of desktop devices being exposed compared to 48K (0.3%) of mobile devices. Shopping scams are the most prevalent scam type, being observed by a total of 10.2M IPs, followed by cryptocurrency scams, observed by 653K IPs. After being observed in the telemetry, the scam domains remain alive for a median of 11 days. In at least 9.2M (13.3%) of all scam observations users followed an advertisement. These ads are largely (59%) hosted on social media, with Facebook being the preferred source.
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