Confidential Computing and Privacy-Preserving Technologies for 6G

The transition to 6G networks brings significant opportunities for new digital services, but also introduces new challenges for security and privacy. Unlike previous generations, 6G will connect a massive number of heterogeneous devices across highly dynamic environments, integrating cloud, edge, IoT, and AI systems into a single continuum. Protecting data in such a setting requires new methods that go beyond the capabilities of traditional security solutions.

Core technological pillars

CONFIDENTIAL6G addresses these challenges by focusing its research on three complementary pillars:

Confidential Computing – Protecting data in use through trusted execution environments (TEEs) and secure enclaves. This ensures sensitive information can be processed without exposing it to unauthorized parties, reducing the risks of internal threats in cloud and edge systems.
Post-Quantum Cryptography (PQC) – Preparing for a future where quantum computing could compromise classical cryptographic methods. The project investigates PQC schemes suitable for both high-performance network functions and constrained devices at the edge.
Confidential Communication – Safeguarding data in transit with end-to-end protections. This includes integrating PQC with blockchain technologies for traceability and access control, ensuring secure communication across diverse and distributed infrastructures.

Together, these technologies provide a foundation for resilient and privacy-preserving 6G infrastructures.

Edge intelligence and federated AI

With the growing role of edge devices in 6G, minimizing data movement is critical for both performance and trust. CONFIDENTIAL6G advances federated AI/ML techniques that allow models to be trained collaboratively across distributed datasets, without centralizing sensitive information. This approach not only improves security but also supports compliance with data sovereignty requirements across different jurisdictions.

Use cases

The project validates its technologies through three representative use cases:

Predictive maintenance in aviation – Using blockchain-based data sharing and federated AI to improve reliability across airline consortia.
Telecom cloud security – Deploying confidential computing platforms to mitigate internal threats and protect customer data in large-scale telecom infrastructures.
Intelligent connected vehicles – Securing mission-critical services such as over-the-air updates, vehicle-to-infrastructure communication, and federated learning for autonomous mobility.

These pilots demonstrate how privacy-preserving and post-quantum technologies can be embedded into real-world 6G environments.

Building trust in 6G

By combining confidential computing, post-quantum cryptography, and federated intelligence, CONFIDENTIAL6G develops an integrated security framework designed to meet the demands of future digital ecosystems. Its outcomes aim to ensure that 6G can deliver innovative services while maintaining strong guarantees of privacy, trust, and resilience.

Confidential Computing and Privacy-Preserving Technologies for 6G