The 3rd International Workshop on Big Data Analysis and Illicit Trends aims to bring together interdisciplinary research on how big data analytics can expose, understand, and counteract illicit and harmful behavior on the Surface, Deep, and Dark Web. While the internet has revolutionized communication and commerce, it also serves as a platform for misinformation, identity fraud, cybercrime, and illicit trade. This workshop focuses on advanced methods to mine data, detect criminal patterns, trace illicit financial flows, and assess the societal impacts of online risks, with a special focus on the combination of artificial intelligence, machine learning, and Cyber Threat Intelligence (CTI). We welcome contributions that offer novel insights, tools, datasets, or frameworks to monitor, analyze, and respond to criminal behavior and misinformation online.

The workshop will be held in conjunction with IEEE Big Data 2026, taking place in Phoenix (Arizona), USA, from December 14-17, 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 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
-Agentic-AI for 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