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

  • Loughborough University
  • University of Bielsko-Biala
  • Poznan University of Economics

Research output: Chapter in Book/Published conference outputConference publication

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.
Original languageEnglish
Title of host publication2025 15th International Conference on Advanced Computer Information Technologies (ACIT)
PublisherIEEE
Pages481-486
Number of pages6
ISBN (Electronic)9798331595449
ISBN (Print)9798331595432
DOIs
Publication statusPublished - 9 Oct 2025
Event2025 15th International Conference on Advanced Computer Information Technologies (ACIT) - Sibenik, Croatia
Duration: 17 Sept 202519 Sept 2025

Publication series

NameProceedings from the International Conference on Advanced Computer Information Technologies (ACIT)
PublisherIEEE
ISSN (Print)2770-5218
ISSN (Electronic)2770-5226

Conference

Conference2025 15th International Conference on Advanced Computer Information Technologies (ACIT)
Period17/09/2519/09/25

Bibliographical note

Copyright © 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Funding

This research was supported by the Horizon 2020 programme [TRACE - AI in countering financial crime and tracing illicit money flows] - Grant Agreement No. 101022004.

FundersFunder number
Horizon 2020 Framework Programme
TRACE101022004

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 16 - Peace, Justice and Strong Institutions
      SDG 16 Peace, Justice and Strong Institutions

    Keywords

    • Digital forensics
    • Europe
    • Collaboration
    • Standardization
    • Real-time systems
    • Proposals
    • Artificial intelligence
    • Computational intelligence
    • Research and development
    • Resilience

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