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CONFIDENTIAL6G: Confidential Computing and Privacy-preserving technologies for 6G

Networks and Connectivity Artificial Intelligence Quantum Computing
CONFIDENTIAL6G aims to develop cryptographic quantum-resistant protocols and security proofs tools, libraries, mechanisms, and architectural blueprints for confidentiality in 6G. 
The project relies on three main pillars:  
  • Cryptography: Cryptographic enablers for confidential computing (fully homomorphic encryption, secure multi-party computation, trusted execution environments) and post-quantum networking. Distributed ledger technology privacy enablers (zero knowledge proofs). Support for embedded edge devices and hardware. 

  • Confidential Computing: via fully homomorphic encryption, secure multi-party computation, and hardware-based trusted execution environments. Collaborative AI/ML. Confidential containers. Remote attestations. Secure enclave abstractions. Secure key distribution. 

  • Confidential Networking: Post-quantum secure network protocols. Secure data sharing and access control. Private blockchain smart contracts, decentralized identifiers, and verifiable credentials. Federated AI/ML orchestration. 
Telefónica's role in this project focuses on the development of secure and trustworthy systems for distributed and federated learning of AI/ML models, developing mechanisms for enhancing the privacy and security of these algorithms, mitigating some of their existing limitations and vulnerabilities. On the other hand, we also lead a use case on vehicular communication leveraging the trustworthy, secure, and privacy-preserving federated learning mechanisms mentioned before.

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