3 citations · 3 across the 3 of their papers we have counts for
4 papers · 1 filter
Securing Filesystems for Confidential Computing
Dimitra Giantsidi, Antoine Delignat-Lavaud, Cédric Fournet +5
Confidential computing protects applications inside Trusted Execution Environments (TEEs), but it leaves storage vulnerable. Even with disk encryption, a malicious cloud provider c…
Transparent Attested DNS for Confidential Computing Services
Antoine Delignat-Lavaud, Cédric Fournet, Kapil Vaswani +3
Confidential services running in hardware-protected Trusted Execution Environments (TEEs) can provide higher security assurance, but this requires custom clients and protocols to d…
VerifiableFL: Verifiable Claims for Federated Learning using Exclaves
Jinnan Guo, Kapil Vaswani, Andrew Paverd +1
In federated learning (FL), data providers jointly train a machine learning model without sharing their training data. This makes it challenging to provide verifiable claims about…
Confidential Machine Learning within Graphcore IPUs
Kapil Vaswani, Stavros Volos, Cédric Fournet +9
We present IPU Trusted Extensions (ITX), a set of experimental hardware extensions that enable trusted execution environments in Graphcore's AI accelerators. ITX enables the execut…