Connecting online criminal behavior with machine learning: Using authorship attribution to analyze and link potential online traffickers

ArXi:2605.04080v1 Announce Type: cross This research investigated how online criminal activities can be better understood and connected using data-driven machine learning methods. Many illegal activities, such as human trafficking and illicit trade, have moved to online platforms where offenders hide behind anonymous accounts and frequently change identities. This makes it difficult for authorities to understand how large these networks are and how different online profiles may be linked.