Detection and Tracking of Drug Trafficking in Encrypted Social Media

Social media platforms are now crucial for the promotion and distribution of illegal drugs. Hashtags increase the likelihood of drug usage by making it simpler for users to participate in drug trafficking. Nonetheless, identifying and controlling drug trafficking activities presents considerable difficulties. Furthermore, the quick legalization of some substances has necessitated a more precise classification of drugs in order to differentiate them from illegal ones. Inspired by these findings, our goal in this study is to create a methodology that uses the most recent developments in artificial intelligence technology to categorize hashtags from postings that advertise illegal narcotics for sale on social media. We offer a semi-supervised deep learning method for categorizing hashtags from posts that promote illegal substances.