Thulitha Senevirathna

This survey examines how Explainable AI (XAI) can strengthen security in 5G and future 6G networks, where AI models increasingly drive tasks such as intrusion detection, traffic classification, PHY-layer authentication, and anomaly detection. While these models offer strong performance, their… Read More »A Survey on XAI for 5G and Beyond Security: Technical Aspects, Challenges and Research Directions

This paper provides a concise overview of how security must evolve as we move toward 6G smart networks, where communication, sensing, and computing become tightly integrated. It highlights that future systems will rely heavily on distributed AI/ML, making the protection… Read More »Advancing Security for 6G Smart Networks and Services

As global connectivity ushers in the next era of communication, 6G networks are poised to revolutionize technology with unprecedented capabilities. These advancements will rely heavily on Artificial Intelligence (AI) and Machine Learning (ML), which are expected to enhance network efficiency,… Read More »Strengthening 6G AI/ML Security: Insights from ROBUST-6G Threat Assessment and Prevention Report

As the world transitions towards the sixth generation (6G) of wireless networks, ensuring robust security and trustworthiness solutions becomes a critical necessity. In this vein, the ROBUST-6G project aims to address key challenges related to security and trustworthiness through a… Read More »Exploring the Future of Secure 6G Networks: Insights from ROBUST-6G Deliverable 2.2

As 6G emerges as a transformative force in digital communication, its ability to seamlessly integrate the digital and physical worlds hinges on robust security frameworks. ROBUST-6G’s Deliverable 2.1, “6G Threat Analysis Report,” lays the groundwork for addressing this pivotal challenge,… Read More »Unveiling the Future of 6G Security with ROBUST-6G’s Threat Analysis