Enhancing European Cyber Forensics: A Computational Intelligence Approach for Detecting Illicit Money Flows

Abstract

Digital financial transactions throughout Europe have proliferated, creating more complex and frequent cyber-enabled financial crimes such as illicit money flows and advanced money laundering operations. Recent cybercrimes necessitate sophisticated cyber forensic methods for their detection and investigation. European law enforcement agencies (LEAs) face significant obstacles when dealing with technology and procedures because they have insufficient computational tool integration while showing varied implementation of artificial intelligence (AI) and lacking essential machine learning (ML) skills. The research investigates current European cyber forensic technology while identifying crucial weaknesses to demonstrate the requirement for using computational intelligence methods. The research draws findings from European LEAs based on empirical data collection. The results demonstrate the potential for AI and ML algorithms to enhance analytic precision and enable automated complex tasks and scalable dataset management.