Chamara Sandeepa

This paper presents SHERPA, an explainability-driven defense framework designed to protect Federated Learning (FL) systems from data poisoning attacks. FL allows distributed devices to collaboratively train a global model without sharing raw data, but this also opens the door for… Read More »SHERPA: Explainable Robust Algorithms for Privacy-Preserved Federated Learning in Future Networks to Defend Against Data Poisoning Attacks

This paper introduces ROBUST-6G, a European research initiative aimed at designing a comprehensive security platform for future 6G networks. As 6G moves toward deeply integrated digital: physical systems, the project focuses on building security mechanisms that are data-driven, automated, trustworthy,… Read More »ROBUST-6G: Smart, Automated, and Reliable Security Service Platform for 6G

As wireless systems evolve toward 6G, AI becomes increasingly central to how networks operate, optimize themselves, and deliver advanced services. But with greater autonomy and complexity comes a critical requirement: the decisions made by AI models must be understandable, transparent,… Read More »Explainable AI for 6G Use Cases: Technical Aspects and Research Challenges