37 citations · 99 across the 14 of their papers we have counts for
4 papers · 1 filter
SecFL: Confidential Federated Learning using TEEs
Do Le Quoc, Christof Fetzer
Federated Learning (FL) is an emerging machine learning paradigm that enables multiple clients to jointly train a model to take benefits from diverse datasets from the clients with…
Perun: Secure Multi-Stakeholder Machine Learning Framework with GPU Support
Wojciech Ozga, Do Le Quoc, Christof Fetzer
Confidential multi-stakeholder machine learning (ML) allows multiple parties to perform collaborative data analytics while not revealing their intellectual property, such as ML sou…
secureTF: A Secure TensorFlow Framework
Do Le Quoc, Franz Gregor, Sergei Arnautov +3
Data-driven intelligent applications in modern online services have become ubiquitous. These applications are usually hosted in the untrusted cloud computing infrastructure. This p…
A practical approach for updating an integrity-enforced operating system
Wojciech Ozga, Do Le Quoc, Christof Fetzer
Trusted computing defines how to securely measure, store, and verify the integrity of software controlling a computer. One of the major challenges that make them hard to be applied…