Understanding Cross-Platform Referral Traffic for Illicit Drug Promotion
Mingming Zha, Zilong Lin, Siyuan Tang, Xiaojing Liao, Yuhong Nan, XiaoFeng Wang
Abstract
The promotion of illegal drugs has become increasingly prevalent on popular social media platforms such as TikTok, Instagram, and YouTube. Within this ecosystem, miscreants utilize cross-platform referral traffic to advertise and promote illicit drugs. They start by posting illicit drug-promoting comments on upstream social media platforms, attracting potential drug buyers, and then redirecting these buyers to downstream platforms where the actual drug sales take place. To the best of our knowledge, little has been done so far to understand this cross-platform referral traffic for illicit drug promotion and selling on social media platforms, not to mention any effort to systematically identify such referral traffic on social media platforms. In this paper, we designed an automated pipeline for detecting illicit referral traffic and identified 154,753 drug-referral comments and 3,253 drug sellers. Based upon the dataset, we presented the first systematic study on the ecosystem of such cross-platform illicit drug promotion and selling businesses, which sheds light on the strategies and campaigns of illicit drug promotion. These findings provide valuable insights into the broader impact of illicit drug trading activities and highlight the need for increased attention to addressing the associated security concerns in social media platforms. CCS Concepts • Security and privacy → Social network security and privacy; Web application security.
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