4 papers
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…
Systematic Use of Random Self-Reducibility against Physical Attacks
Ferhat Erata, TingHung Chiu, Anthony Etim +7
This work presents a novel, black-box software-based countermeasure against physical attacks including power side-channel and fault-injection attacks. The approach uses the concept…