Evolving AI Cyber Security: Adaptive Detection and Mitigation 

About the Special Session

This special session focuses on Evolving AI Cyber Security: Adaptive Detection and Mitigation and will be held as part of IEEE EAIS 2026.

Cyber security has become a moving target where attackers constantly evolve tactics while organisations continuously update infrastructure. Static detection models degrade quickly after deployment. This session aims to explore adaptive, evolving, and intelligent cyber defence systems capable of learning continuously in dynamic environments.

We invite contributions addressing evolving and adaptive intelligent systems for cyber defence that can handle concept drift, streaming data, adversarial behaviour, and real-time mitigation.

Topics of Interest

- Continual and lifelong learning for cybersecurity

- Concept drift detection in security data

- Adaptive intrusion detection systems

- Online anomaly detection

- Adversarial machine learning

- Human-in-the-loop security

- Federated learning for cyber defence

- Explainable AI for cybersecurity

- Adaptive incident response

- Privacy-preserving analytics

- Evaluation benchmarks for evolving threats

- Security for LLM-based systems

Organizers

Lead Organizer

Dr Mujeeb Ur Rehman (SMIEEE)

Associate Professor, De Montfort University, UK

Email: mujeeb.rehman@dmu.ac.uk

Co-Organizers

Prof. Sohail Khalid – University of Management and Technology, Pakistan

Dr Lipika Deka – De Montfort University, UK

Submission Instructions

Authors should submit papers through the IEEE EAIS 2026 submission system and select the special session:

"Evolving AI Cyber Security: Adaptive Detection and Mitigation"

All submissions will undergo peer review and accepted papers will appear in IEEE proceedings.