The 2nd Workshop on Big Data Analysis and Illicit Trends (b&it or “BANDIT”) offers a platform for researchers, practitioners, and policymakers to share innovative work towards understanding and addressing illicit activities through big data analytics. The workshop focuses on interdisciplinary approaches that leverage data science, machine learning, and intelligence techniques to uncover hidden patterns in cybercrime and other forms of illicit behavior.
This workshop represents an opportunity for the exploratory depiction of the current state of practice along the lines of actionable Cyber Threat Intelligence (CTI), countermeasures to threats and Open Source INTelligence (OSINT), as well as a call to action for further work and transfer of theoretical-practical research around cybersecurity from academia towards practitioners from industry.
The workshop will be held in conjunction with IEEE Big Data 2025, taking place in Macau, China, from December 8–11, 2025.
This is a Hybrid event, allowing for both in-person presentations and remote participation
Important Dates
Consider 23:59 Anywhere on Earth (AoE) for every date below:
- Submission (Cycle 1): Sep 14, 2025
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Notification of Acceptance (Cycle 1): Oct 05, 2025
- Submission (Cycle 2): Oct 26, 2025
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Notification of Acceptance (Cycle 2): Nov 16, 2025
- Camera-ready: Nov 23, 2025
- Workshop & Conference: Dec 08–11, 2025
Submission site: https://wi-lab.com/cyberchair/2025/bigdata25/scripts/ws_submit.php
Topics of Interest
The topics of interest related to the workshop include, but are not limited to:
Cyber Threat Intelligence and Automation
- Actionable Cyber Threat Intelligence: From Detection to Response
- Automation of Threat Analysis and Threat Hunting
- Best Practices and Frameworks for Cyber Threat Intelligence
- AI-Driven Automation for Threat Detection in Complex Environments
- Neurosymbolic AI in Cyber Threat Intelligence
- Ontology-based Methods in Cyber Threat Intelligence
Artificial Intelligence & Machine Learning on Cybercrime Marketplaces
- AI and Machine Learning for Criminal Pattern Analysis
- AI Methods for CAPTCHA-Solving and Circumvention Techniques
- Big Data Analysis of User Behaviour in Dark Web Marketplaces
- Big Data Analysis of Criminal Behavior in Social Media
- Big Data Analysis for Criminal Networks
- Big Data Blockchain Analysis and Bitcoin laundering
- Explainable AI in Support of Criminal Investigations and Prosecution
- Social Media Privacy and Security
- Societal Impact of Cybercriminal Behaviour
- Trend Analysis of Drugs and New Psychoactive Substances (NPS)
Misinformation & Online Influence
- Analysis of the Role and the Impact of Misinformation in Online Platforms
- Identification of Disinformation Campaigns in Online Platforms with AI.
- Disinformation and Echo Chambers
- Study of online debates to identify segregation, hate speech, and extreme polarization
- The influence of coordinated automated account networks in online communities
Organising Committee
- Cristoffer Leite - Eindhoven University of Technology (TU/e) -
- Indika Kumara - Tilburg University (TiU) -
- Giuseppe Cascavilla - Tilburg University (TiU) -
- Alexios Lekidis - University of Thessaly -
Steering Committee
- Ana Isabel Barros - Dutch Organisation for Applied Scientific Research (TNO), Tilburg University (TiU)
- Damian Tamburri - Università del Sannio, Tilburg University (TiU), NXP
- João Gondim - University of Brasilia (UnB)
- Michele Campobasso - Forescout (Vedere Labs)
- Robson de Albuquerque - University of Brasilia (UnB)
- Willem-Jan v.d Heuvel - Tilburg University (TiU)
