37 citations · 169 across the 8 of their papers we have counts for
8 papers
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.…
POSE: Practical Off-chain Smart Contract Execution
Tommaso Frassetto, Patrick Jauernig, David Koisser +4
Smart contracts enable users to execute payments depending on complex program logic. Ethereum is the most notable example of a blockchain that supports smart contracts leveraged fo…
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…
V'CER: Efficient Certificate Validation in Constrained Networks
David Koisser, Patrick Jauernig, Gene Tsudik +1
We address the challenging problem of efficient trust establishment in constrained networks, i.e., networks that are composed of a large and dynamic set of (possibly heterogeneous)…
TheHuzz: Instruction Fuzzing of Processors Using Golden-Reference Models for Finding Software-Exploitable Vulnerabilities
Aakash Tyagi, Addison Crump, Ahmad-Reza Sadeghi +4
The increasing complexity of modern processors poses many challenges to existing hardware verification tools and methodologies for detecting security-critical bugs. Recent attacks…
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…
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…
GrandDetAuto: Detecting Malicious Nodes in Large-Scale Autonomous Networks
Tigist Abera, Ferdinand Brasser, Lachlan J. Gunn +3
Autonomous collaborative networks of devices are rapidly emerging in numerous domains, such as self-driving cars, smart factories, critical infrastructure, and Internet of Things i…