Use of AIML Powered Algorithm to Detect Illicit Activity Inside the Bitcoin Organisation

Abstract

When the technology behind Bitcoin was first revealed in the form of a white paper in 2009 and the corresponding reference implementation was released subsequently. Bitcoin has been accused by critics for pro- viding and shielding a sanctuary to criminal operations. A wide range of illegal means are used by people taking cover behind the sweeping of namelessness (anonymity). Revealing these substances is most crucial point for legal examinations. State-of-the-art techniques use Artificial Intelligence for comparing and identifying these actors but concentrate on a limited number of illegal trades. The ongoing research embarks to resolve the issue by executing a machine-learning enabled auto- mated rule based classification for various types of illegal activities, viz., ponzi schemes, blackmailers, frauds, scams, extortionists, spam- mers, gambling websites, darknet markets, terrorists and sextortionists.