activity
20172026
most citedsecureTF: A Secure TensorFlow Framework

37 citations · 97 across the 6 of their papers we have counts for

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Showing cs.CRShow all

5 papers · 1 filter

cs.CR2026

EnclaveX: End-to-End Confidential AI with CPU/GPU TEEs

Robert Schambach, Quoc Do Le, Sergei Arnautov +1

Large Language Models (LLMs) have rapidly proliferated, driving widespread adoption of AI applications. Most deployments rely on centralized infrastructures such as Microsoft Azure…

cs.CR2021★ 37 cited

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…

cs.CR2020

Trust Management as a Service: Enabling Trusted Execution in the Face of Byzantine Stakeholders

Franz Gregor, Wojciech Ozga, Sébastien Vaucher +7

Trust is arguably the most important challenge for critical services both deployed as well as accessed remotely over the network. These systems are exposed to a wide diversity of t…

cs.CR2019★ 35 cited

TensorSCONE: A Secure TensorFlow Framework using Intel SGX

Roland Kunkel, Do Le Quoc, Franz Gregor +3

Machine learning has become a critical component of modern data-driven online services. Typically, the training phase of machine learning techniques requires to process large-scale…

cs.CR2017★ 11 cited

Slick: Secure Middleboxes using Shielded Execution

Bohdan Trach, Alfred Krohmer, Sergei Arnautov +3

Cloud computing offers the economies of scale for computational resources with the ease of management, elasticity, and fault tolerance. To take advantage of these benefits, many en…