activity
20172025
most citedsecureTF: A Secure TensorFlow Framework

37 citations · 120 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CR2025

TICAL: Trusted and Integrity-protected Compilation of AppLications

Robert Krahn, Nikson Kanti Paul, Franz Gregor +4

During the past few years, we have witnessed various efforts to provide confidentiality and integrity for applications running in untrusted environments such as public clouds. In m…

cs.CR2023

SinClave: Hardware-assisted Singletons for TEEs

Franz Gregor, Robert Krahn, Do Le Quoc +1

For trusted execution environments (TEEs), remote attestation permits establishing trust in software executed on a remote host. It requires that the measurement of a remote TEE is…

cs.CR2022★ 2 cited

Synergia: Hardening High-Assurance Security Systems with Confidential and Trusted Computing

Wojciech Ozga, Rasha Faqeh, Do Le Quoc +3

High-assurance security systems require strong isolation from the untrusted world to protect the security-sensitive or privacy-sensitive data they process. Existing regulations imp…

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★ 3 cited

TEEMon: A continuous performance monitoring framework for TEEs

Robert Krahn, Donald Dragoti, Franz Gregor +6

Trusted Execution Environments (TEEs), such as Intel Software Guard eXtensions (SGX), are considered as a promising approach to resolve security challenges in clouds. TEEs protect…

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.DC2019★ 14 cited

PubSub-SGX: Exploiting Trusted Execution Environments for Privacy-Preserving Publish/Subscribe Systems

Sergei Arnautov, Andrey Brito, Pascal Felber +9

This paper presents PUBSUB-SGX, a content-based publish-subscribe system that exploits trusted execution environments (TEEs), such as Intel SGX, to guarantee confidentiality and in…

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.DC2018★ 18 cited

SecureCloud: Secure Big Data Processing in Untrusted Clouds

Florian Kelbert, Franz Gregor, Rafael Pires +7

We present the SecureCloud EU Horizon 2020 project, whose goal is to enable new big data applications that use sensitive data in the cloud without compromising data security and pr…

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…