5 papers
Fault Attacks on ML-based Quantum Control and Error Correction
Anthony Etim, Jakub Szefer
Machine-learning (ML) models are increasingly used in quantum computing systems to discriminate multi-qubit readouts, mitigate correlated readout errors, and decode quantum error-c…
Snowball Adversarial Attack on Traffic Sign Classification
Anthony Etim, Jakub Szefer
Adversarial attacks on machine learning models often rely on small, imperceptible perturbations to mislead classifiers. Such strategy focuses on minimizing the visual perturbation…
Adversarial Universal Stickers: Universal Perturbation Attacks on Traffic Sign using Stickers
Anthony Etim, Jakub Szefer
Adversarial attacks on deep learning models have proliferated in recent years. In many cases, a different adversarial perturbation is required to be added to each image to cause th…
Fall Leaf Adversarial Attack on Traffic Sign Classification
Anthony Etim, Jakub Szefer
Adversarial input image perturbation attacks have emerged as a significant threat to machine learning algorithms, particularly in image classification setting. These attacks involv…
Time Traveling to Defend Against Adversarial Example Attacks in Image Classification
Anthony Etim, Jakub Szefer
Adversarial example attacks have emerged as a critical threat to machine learning. Adversarial attacks in image classification abuse various, minor modifications to the image that…