Secure and Reliable End-to-End Network Slicing for 5G and Beyond Mobile Networks

Project Description

Network slicing partitions the physical network into several fit-for-purpose virtual networks with different degrees of isolation and quality of service to meet application requirements. However, it introduces vulnerabilities inherent to softwarization and virtualization technologies that could lead to compromised services. This project aims to secure 5G network slices end-to-end while meeting high levels of performance, flexibility, and reliability. The objectives include: (1) Artificial Intelligence (AI) based threat detection, and automatic deployment of countermeasures; (2) Security-by-design end-to-end network slice orchestration, including ZeroTrust attestation of underlying software supply chain; (3) Softwarized, high-performance and scalable Multi-access Edge Computing (MEC) platform to facilitate network telemetry, AI-based analytics, and on-demand orchestration of security functions, at the network edge. The MEC and AI solutions will be integrated into a large-scale 5G testbed.

Project Objectives and Outcomes



Sponsors and Partners

Department of Defense
University of Regina