The work of security researchers from the National Security Institute (NSI) at Stony Brook University was featured in WIRED magazine's March 13, 2017 article, Listen to ‘Tech Support’ Scam Calls That Bilk Victims Out of Millions.
The scam that NSI researchers set their sights on, which many of us have experienced firsthand, pretends to be a "virus" that has taken over a user's computer blocking access to documents, programs, and photos. The scammers moves to the next level by stating that they are "Microsoft Support" and that they can fix the victim's computer if the victim pays a fee. Since determining how the scam works is more than half the battle, security researchers at NSI were focused and patiently visited tens of thousands of web pages that ensare victims.
The research paper Dial one for Scam: A Large-Scale Analysis of Technical Support Scams highlighted in WIRED was presented and recognized with a Distinguished Paper award at the Network and Distributed Systems Security Symposium. In the WIRED article CS faculty and NSI researchers Nick Nikiforakis, Najmeh Miramirkhani, and Oleksii Starov, detail how they mapped out fraudulent tech support schemes using an automatic web-crawling tool. After becoming a "victim", the NSI researchers took it a step further by spending countless hours on the phone with the scammers pretending to be unsuspecting victims.
In the article, Nikiforakis says that their goal was to find out "how big this scam was, how do scammers reach people, and when they get them on the phone, how do they convince them" to spend hundreds of dollars on fake fixes.
Nikiforakis' advice? “Don’t trust what your browser tells you about the safety and security of your system. People need to understand there’s no legitimate scenario where your computer will start beeping and ask you to call a toll-free number.”
Their research offers new hope for preventing security scams which count revenue in the tens of millions of dollars. It also offers methods for identifying these large scam call centers as well as methods to use to attack the problem. This work was supported by the Office of Naval Research (ONR) under grant N00014-16-1- 2264, by the National Science Foundation (NSF) under grants CNS-1617902 and CNS-1617593, and by the Cyber Research Institute in Rome, New York.