2 citations · 7 across the 13 of their papers we have counts for
13 papers
Differential Zonotopes for Verifying Global Robustness of DNNs
Anagha Athavale, Samuel Teuber, Matteo Maffei +3
The robustness of deep neural networks (DNNs) is critical in security-sensitive applications, where small input perturbations should not alter model predictions. This property is c…
Encrypted Neural Networks without Overflows
Philipp Kern, Lorenzo Rovida, Samuel Teuber +3
The popular Cheon-Kim-Kim-Song (CKKS) scheme enables efficient private inference in neural networks by evaluating them on encrypted data. Since CKKS only supports addition, multipl…
Compositional Neural-Cyber-Physical System Verification in the Interactive Theorem Prover of Your Choice
Matthew L. Daggitt, Ekaterina Komendantskaya, Alistair Sirman +4
Formal verification of neuro-symbolic cyber-physical systems, such as drones, medical devices and robots, is complicated. Neural components must be trained to be optimal with respe…
Of Good Demons and Bad Angels: Guaranteeing Safe Control under Finite Precision
Samuel Teuber, Debasmita Lohar, Bernhard Beckert
As neural networks (NNs) become increasingly prevalent in safety-critical neural network-controlled cyber-physical systems (NNCSs), formally guaranteeing their safety becomes cruci…
Heterogeneous Dynamic Logic: Provability Modulo Program Theories
Samuel Teuber, Mattias Ulbrich, André Platzer +1
Formally specifying, let alone verifying, properties of systems involving multiple programming languages is inherently challenging. We introduce Heterogeneous Dynamic Logic (HDL),…
Verification of Autonomous Neural Car Control with KeYmaera X
Enguerrand Prebet, Samuel Teuber, André Platzer
This article presents a formal model and formal safety proofs for the ABZ'25 case study in differential dynamic logic (dL). The case study considers an autonomous car driving on a…
Next Steps in LLM-Supported Java Verification
Samuel Teuber, Bernhard Beckert
Recent work has shown that Large Language Models (LLMs) are not only a suitable tool for code generation but also capable of generating annotation-based code specifications. Scalin…
Revisiting Differential Verification: Equivalence Verification with Confidence
Samuel Teuber, Philipp Kern, Marvin Janzen +1
When validated neural networks (NNs) are pruned (and retrained) before deployment, it is desirable to prove that the new NN behaves equivalently to the (original) reference NN. To…
Provably Safe Neural Network Controllers via Differential Dynamic Logic
Samuel Teuber, Stefan Mitsch, André Platzer
While neural networks (NNs) have potential as autonomous controllers for Cyber-Physical Systems, verifying the safety of NN based control systems (NNCSs) poses significant challeng…
Quantifying Software Correctness by Combining Architecture Modeling and Formal Program Analysis
Florian Lanzinger, Christian Martin, Frederik Reiche +3
Most formal methods see the correctness of a software system as a binary decision. However, proving the correctness of complex systems completely is difficult because they are comp…
An Information-Flow Perspective on Algorithmic Fairness
Samuel Teuber, Bernhard Beckert
This work presents insights gained by investigating the relationship between algorithmic fairness and the concept of secure information flow. The problem of enforcing secure inform…
Geometric Path Enumeration for Equivalence Verification of Neural Networks
Samuel Teuber, Marko Kleine Büning, Philipp Kern +1
As neural networks (NNs) are increasingly introduced into safety-critical domains, there is a growing need to formally verify NNs before deployment. In this work we focus on the fo…
An Incremental Abstraction Scheme for Solving Hard SMT-Instances over Bit-Vectors
Samuel Teuber, Marko Kleine Büning, Carsten Sinz
Decision procedures for SMT problems based on the theory of bit-vectors are a fundamental component in state-of-the-art software and hardware verifiers. While very efficient in gen…