Analyzing Ground-Truth Data of Mobile Gambling Scams
Geng Hong, Zhemin Yang, Sen Yang, Xiaojing Liao, Xiaolin Du, Min Yang, Haixin Duan
摘要
With the growth of mobile computing techniques, mobile gambling scams have seen a rampant increase in the recent past. In mobile gambling scams, miscreants deliver scamming messages via mobile instant messaging, host scam gambling platforms on mobile apps, and adopt mobile payment channels. To date, there is little quantitative knowledge about how this trending cybercrime operates, despite causing daily fraud losses estimated at more than {\$$522,262 USD. This paper presents the first empirical study based on ground-truth data of mobile gambling scams, associated with 1,461 scam incident reports and 1,487 gambling scam apps, spanning from January 1, 2020 to December 31, 2020. The qualitative and quantitative analysis of this ground-truth data allows us to characterize the operational pipeline and full fraud kill chain of mobile gambling scams. In particular, we study the social engineering tricks used by scammers and reveal their effectiveness. Our work provides a systematic analysis of 1,068 confirmed Android and 419 iOS scam apps, including their development frameworks, declared permissions, compatibility, and backend network infrastructure. Perhaps surprisingly, our study unveils that public online app generators have been abused to develop gambling scam apps. Our analysis reveals several payment channels (ab)used by gambling scam app and uncovers a new type of money mule-based payment channel with the average daily gambling deposit of $$400,000 USD. Our findings enable a better understanding of the mobile gambling scam ecosystem, and suggest potential avenues to disrupt these scam activities.
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