Publications

RoFL: Robustness of Secure Federated Learning.

Hidde Lycklama*, Lukas Burkhalter*, Alexander Viand, Nicolas Küchler, Anwar Hithnawi

IEEE Security and Privacy (Oakland), 2023 (*same contribution)

VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely?.

Jiawei Jiang, Lukas Burkhalter, Fangcheng Fu, Bolin Ding, Bo Du, Anwar Hithnawi, Bo Li, Ce Zhang

NeurIPS (Spotlight) 2022

Cryptographic Auditing for Collaborative Learning

Hidde Lycklama, Nicolas Küchler, Alexander Viand, Emanuel Opel, Lukas Burkhalter, Anwar Hithnawi

ML Safety Workshop at NeurIPS 2022

Zeph: Cryptographic Enforcement of End-to-End Data Privacy.

Lukas Burkhalter*, Nicolas Küchler*, Alexander Viand, Hossein Shafagh, Anwar Hithnawi

USENIX OSDI 2021

Droplet: Decentralized Authorization and Access Control for Encrypted Data Streams

Hossein Shafagh, Lukas Burkhalter, Sylvia Ratnasamy, Anwar Hithnawi

USENIX Security 2020

TimeCrypt: Encrypted Data Stream Processing at Scale with Access Control

Lukas Burkhalter, Anwar Hithnawi, Alexander Viand, Hossein Shafagh, Sylvia Ratnasamy

USENIX NSDI 2020

Robust Secure Aggregation for Privacy-Preserving Federated Learning with Adversaries

Lukas Burkhalter, Alexander Viand, Matthias Lei, Hossein Shafagh, Anwar Hithnawi

PPML Workshop at CCS 2019

Secure Sharing of Partially Homomorphic Encrypted IoT Data.

Hossein Shafagh, Anwar Hithnawi, Lukas Burkhalter, Pascal Fischli, Simon Duquennoy

ACM SenSys 2017

Towards Blockchain-based Auditable Storage and Sharing of IoT Data.

Hossein Shafagh, Lukas Burkhalter, Anwar Hithnawi, Simon Duquennoy

CCSW Workshop at CCS 2017