activity
20182022
most citedOffline Model Guard: Secure and Private ML on Mobile Devices

34 citations · 104 across the 7 of their papers we have counts for

collaborators

7 papers

cs.SE2022★ 30 cited

DARWIN: Survival of the Fittest Fuzzing Mutators

Patrick Jauernig, Domagoj Jakobovic, Stjepan Picek +2

Fuzzing is an automated software testing technique broadly adopted by the industry. A popular variant is mutation-based fuzzing, which discovers a large number of bugs in practice.…

cs.CR2022★ 7 cited

Trusted Container Extensions for Container-based Confidential Computing

Ferdinand Brasser, Patrick Jauernig, Frederik Pustelnik +2

Cloud computing has emerged as a corner stone of today's computing landscape. More and more customers who outsource their infrastructure benefit from the manageability, scalability…

cs.CR2021

Chunked-Cache: On-Demand and Scalable Cache Isolation for Security Architectures

Ghada Dessouky, Alexander Gruler, Pouya Mahmoody +2

Shared cache resources in multi-core processors are vulnerable to cache side-channel attacks. Recently proposed defenses have their own caveats: Randomization-based defenses are vu…

cs.CR2020★ 27 cited

CURE: A Security Architecture with CUstomizable and Resilient Enclaves

Raad Bahmani, Ferdinand Brasser, Ghada Dessouky +4

Security architectures providing Trusted Execution Environments (TEEs) have been an appealing research subject for a wide range of computer systems, from low-end embedded devices t…

cs.CR2020★ 3 cited

Trustworthy AI Inference Systems: An Industry Research View

Rosario Cammarota, Matthias Schunter, Anand Rajan +26

In this work, we provide an industry research view for approaching the design, deployment, and operation of trustworthy Artificial Intelligence (AI) inference systems. Such systems…

cs.CR2020★ 34 cited

Offline Model Guard: Secure and Private ML on Mobile Devices

Sebastian P. Bayerl, Tommaso Frassetto, Patrick Jauernig +5

Performing machine learning tasks in mobile applications yields a challenging conflict of interest: highly sensitive client information (e.g., speech data) should remain private wh…

cs.NI2018★ 3 cited

Towards Fine Grained Network Flow Prediction

Patrick Jahnke, Emmanuel Stapf, Jonas Mieseler +2

One main challenge for the design of networks is that traffic load is not generally known in advance. This makes it hard to adequately devote resources such as to best prevent or m…