Toward Defending Adversarial Patch Attacks With Mask-Reconstruction-Assisted Adversarial Training
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2025.3629619
Abstract: Adversarial patch attacks pose a significant threat to deep learning models in real-world applications, such as autonomous driving, due to their physical feasibility and ease of deployment. Although several defenses exist, they often have limitations,… read more here.
Keywords: patch; adversarial training; mask reconstruction; patch attacks ... See more keywords
Cost-effective and robust adversarial patch attacks in real-world scenarios
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Electronic Imaging"
DOI: 10.1117/1.jei.34.3.033003
Abstract: Abstract. Deep neural networks (DNNs) are crucial in self-driving car technology but are vulnerable to adversarial attacks that manipulate visual input to mislead decision-making processes. Traditional physical adversarial attacks, such as patch-based methods, often use… read more here.
Keywords: patch; robust adversarial; effective robust; patch attacks ... See more keywords