Welcome to BANDIT - Workshop on Big data analysis AND Illicit Trends

December 14-17, 2026 @ Phoenix, Arizona, USA – Held with 2026 IEEE International Conference on Big Data (IEEE BigData 2026)


The 3rd 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 2026, taking place in Phoenix, Arizona, USA from December 14-17, 2026.

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 due (full and short papers): Oct 26, 2026

Notification of Acceptance: Nov 7, 2026

Camera-ready: Nov 13, 2026

Workshop & Conference: Dec 14–17, 2026

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)
AI & Data-driven Defense of Networked Systems
  • Data-driven Adaptive Moving-Target Defense using Large-Scale Threat Intelligence
  • Scalable AI-based Threat/Intrusion Detection in 5G/6G Data Streams
  • Big Data analytics for secure vehicular network communications
  • LLM-driven Threat Intelligence and adversarial defense at scale
  • Big Data-enabled Intrusion Tolerance for Cyber-Physical systems
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

  • Júlio Mendonça - Tilburg University (TiU) -
  • 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