Zeph: Cryptographic Enforcement of End-to-End Data Privacy. - Lukas Burkhalter; Nicolas Küchler; Alexander Viand; Hossein Shafagh; Anwar Hithnawi (OSDI, 2021)

RoFL: Attestable Robustness for Secure Federated Learning. - Lukas Burkhalter; Hidde Lycklama; Alexander Viand; Nicolas Küchler; Anwar Hithnawi (CoRR, 2021)

RoFL: Robustness of Secure Federated Learning. - Hidde Lycklama; Lukas Burkhalter; Alexander Viand; Nicolas Küchler; Anwar Hithnawi (SP, 2023)

Cohere: Privacy Management in Large Scale Systems. - Nicolas Küchler; Emanuel Opel; Hidde Lycklama; Alexander Viand; Anwar Hithnawi (CoRR, 2023)

Cohere: Managing Differential Privacy in Large Scale Systems. - Nicolas Küchler; Emanuel Opel; Hidde Lycklama; Alexander Viand; Anwar Hithnawi (SP, 2024)

Holding Secrets Accountable: Auditing Privacy-Preserving Machine Learning. - Hidde Lycklama; Alexander Viand; Nicolas Küchler; Christian Knabenhans; Anwar Hithnawi (USENIX Security Symposium, 2024)

Artemis: Efficient Commit-and-Prove SNARKs for zkML. - Hidde Lycklama; Alexander Viand; Nikolay Avramov; Nicolas Küchler; Anwar Hithnawi (CoRR, 2024)

DPolicy: Managing Privacy Risks Across Multiple Releases with Differential Privacy. - Nicolas Küchler; Alexander Viand; Hidde Lycklama; Anwar Hithnawi (SP, 2025)

Architectural Backdoors for Within-Batch Data Stealing and Model Inference Manipulation. - Nicolas Küchler; Ivan Petrov; Conrad Grobler; Ilia Shumailov (CoRR, 2025)