As part of the ENSURE-6G research and innovation programme, a two-month secondment was undertaken at Z-RED L.P., which is a research organisation specialising in interdisciplinary, human-centred AI design. The first phase of this secondment focused on developing the conceptual and methodological foundation for energy-aware trustworthy AI frameworks in the context of 6G network security. The activity contributes directly to Work Package 3 (WP3) – Innovative privacy solutions for 6G with legal and ethical consideration, and more specifically to Task 3.1, which addresses the design of privacy-preserving and ethically compliant AI/ML-enabled intrusion detection systems. The work supports ENSURE-6G’s objective to establish trustworthy, resilient, and regulation-aligned security architectures for next-generation networks.
Building a Foundation for Energy-Aware Trustworthy AI
During the secondment, the focus was on establishing a structured framework that integrates privacy, fairness, and energy efficiency into a unified design approach for AI-driven 6G intrusion detection. The research began with a comprehensive review of current AI/ML techniques in distributed and federated network security, identifying key challenges in meeting privacy, fairness, and sustainability requirements simultaneously. Based on these findings, a set of design and compliance requirements was developed, addressing data protection, explainability, human oversight, and energy optimisation.
Each requirement was systematically mapped to corresponding provisions within the General Data Protection Regulation (GDPR), the EU AI Act, and relevant IEEE 7000-series standards. This alignment ensures traceability from ethical and legal principles to specific technical safeguards, reinforcing ENSURE-6G’s commitment to compliance-by-design and standardisation-readiness. A key outcome of this first phase is the development of an initial optimisation framework capable of balancing multiple objectives — such as detection accuracy, fairness, and energy consumption — using multi-objective evolutionary algorithms (NSGA-II). This approach sets the stage for the practical implementation of energy-aware trustworthy AI mechanisms within 6G security infrastructures.
Collaboration with Z-RED and Knowledge Exchange
The secondment fostered close collaboration between academic and industrial partners, enabling a bidirectional exchange of expertise. The integration of Z-RED’s applied research philosophy – emphasising ethical design, sustainability, and user-centric system thinking – helped shape the framework into a multi-disciplinary solution grounded in both theory and practice. Regular research sessions and internal workshops allowed for iterative refinement of the framework, ensuring that it reflects both ENSURE-6G’s research vision and Z-RED’s industrial application perspective.
Towards Implementation and Validation
The secondment concluded with a clear roadmap for implementation, which will be the focus of the second phase. The upcoming work will translate the conceptual model into operational tools, validate them across representative ENSURE-6G use cases, and develop visual analytics dashboards to monitor energy, fairness, and privacy metrics in real time. These next steps will help ensure that the resulting solutions are technically robust, regulatory-compliant, and practically deployable, reinforcing ENSURE-6G’s mission to deliver trustworthy, human-centric, and sustainable AI solutions for future communication systems.
Contributed by Dr. Adamantios Bampoulas, University College Dublin (UCD),
in collaboration with Z-RED L.P., under Work Package 3 (Task 3.1).
