CONFIDENTIAL6G delivered architectural concepts, prototypes, performance evaluations and security analyses that extend work in post-quantum cryptography, confidential computing and privacy-preserving networking. Rather than full end-to-end products, the outcomes are positioned as validated building blocks, design guidelines and experimental evidence for reuse. Within the Confidential Toolkit, the consortium benchmarked PQ-secure TLS 1.3 in realistic 5G/6G settings, provided a migration roadmap, optimised homomorphic encryption (including TFHE), and introduced Aloha-HE, a client-side CKKS hardware accelerator achieving major speed-ups. The project also advanced zero-knowledge proofs, verifiable secret sharing and verifiable computation supporting privacy-preserving collaborative AI/ML. The Blockchain Toolkit added decentralised identity mechanisms (DIDs, Verifiable and Anonymous Credentials), encrypted DID-bound communication/storage, and feasibility designs for FHE-enabled smart-contract logic, enabling GDPR-compliant authentication, auditability and programmable trust in heterogeneous 6G environments. In confidential computing, CONFIDENTIAL6G designed a platform-agnostic architecture integrating hardware abstraction, remote attestation and attested TLS. AI/ML workloads were demonstrated across heterogeneous TEEs (AMD SEV-SNP, Intel TDX) without refactoring, with exploration of ARM orchestration and RISC-V enclaves. Performance showed attestation in tens of milliseconds and minimal ML slowdowns, while confidential-container orchestration overheads remained modest (~4%). In confidential networking, the project combined decentralised data sharing, identity-anchored access control and trusted orchestration to enable federated AI/ML with local data retention. This was validated through pilots in airline maintenance, telecom insider-threat mitigation and connected vehicles with secure OTA updates.
