3 papers
cs.LG2026
Almost for Free: Crafting Adversarial Examples with Convolutional Image Filters
Alexander Warnecke, Konrad Rieck
Adversarial examples in machine learning are typically generated using gradients, obtained either directly through access to the model or approximated via queries to it. In this pa…
cs.LG2026
Manipulating Feature Visualizations with Gradient Slingshots
Dilyara Bareeva, Marina M. -C. Höhne, Alexander Warnecke +5
Feature Visualization (FV) is a widely used technique for interpreting concepts learned by Deep Neural Networks (DNNs), which synthesizes input patterns that maximally activate a g…
cs.CR2025
Evil from Within: Machine Learning Backdoors through Hardware Trojans
Alexander Warnecke, Julian Speith, Jan-Niklas Möller +2
Backdoors pose a serious threat to machine learning, as they can compromise the integrity of security-critical systems, such as self-driving cars. While different defenses have bee…