Results 11 to 20 of about 5,384 (200)

Ally patches for spoliation of adversarial patches [PDF]

Journal of Big Data, 2019
Adversarial attacks represent a serious evolving threat to the operation of deep neural networks. Recently, adversarial algorithms were developed to facilitate hallucination of deep neural networks for ordinary attackers.
Alaa E. Abdel-Hakim
doaj   +2 more sources

IPatch: a remote adversarial patch

Cybersecurity, 2023
Applications such as autonomous vehicles and medical screening use deep learning models to localize and identify hundreds of objects in a single frame. In the past, it has been shown how an attacker can fool these models by placing an adversarial patch ...
Yisroel Mirsky
doaj   +3 more sources

Investigation of the Robustness and Transferability of Adversarial Patches in Multi-View Infrared Target Detection [PDF]

Journal of Imaging
This paper proposes a novel adversarial patch-generation method for infrared images, focusing on enhancing the robustness and transferability of infrared adversarial patches. To improve the flexibility and diversity of the generation process, a Bernoulli
Qing Zhou, Zhongchen Zhou, Zhaoxiang Zhang, Wei Luo, Feng Xiao, Sijia Xia, Chunjia Zhu, Long Wang   +7 more
doaj   +2 more sources

Segment and Recover: Defending Object Detectors Against Adversarial Patch Attacks [PDF]

Journal of Imaging
Object detection is used to automatically identify and locate specific objects within images or videos for applications like autonomous driving, security surveillance, and medical imaging.
Haotian Gu, Hamidreza Jafarnejadsani
doaj   +2 more sources

Localized Query Attack Toward Transformer-Based Visible Object Detectors [PDF]

Sensors
Transformer-based detectors have demonstrated exceptional accuracy in visible-object detection tasks. However, adversarial patches, specific types of adversarial examples, can disrupt these detectors by introducing unrestricted perturbations into ...
Yang Wang, Ang Li, Zhen Yang, Xunyun Liu
doaj   +2 more sources

Evaluating gait system vulnerabilities through PPO and GAN-generated adversarial attacks [PDF]

Scientific Reports
This study delves into the vulnerabilities of deep learning-based gait recognition systems against adversarial attacks, a critical issue considering the increasing reliance on these technologies in high-security environments.
El Mehdi Saoudi, Jaafar Jaafari, Said Jai Andaloussi   +2 more
doaj   +2 more sources

Traversing the subspace of adversarial patches

Machine Vision and Applications
Abstract Despite ongoing research on the topic of adversarial examples in deep learning for computer vision, some fundamentals of the nature of these attacks remain unclear. As the manifold hypothesis posits, high-dimensional data tends to be part of a low-dimensional manifold.
Jens Bayer, Stefan Becker, Jürgen Beyerer   +2 more
exaly   +4 more sources

Benchmarking Adversarial Patch Selection and Location

Mathematics
Adversarial patch attacks threaten the reliability of modern vision models. We present PatchMap, the first spatially exhaustive benchmark of patch placement, built by evaluating over 1.5×108 forward passes on ImageNet validation images.
Shai Kimhi, Moshe Kimhi, Avi Mendelson
doaj   +3 more sources

An information-theoretic perspective of physical adversarial patches [PDF]

Neural Networks
Real-world adversarial patches were shown to be successful in compromising state-of-the-art models in various computer vision applications. Most existing defenses rely on analyzing input or feature level gradients to detect the patch. However, these methods have been compromised by recent GAN-based attacks that generate naturalistic patches.
Ihsen Alouani, Anouar Ben Khalifa, Mohamed Ali Mahjoub   +2 more
exaly   +5 more sources

Robust Adversarial Attack Against Explainable Deep Classification Models Based on Adversarial Images With Different Patch Sizes and Perturbation Ratios

IEEE Access, 2021
In recent years, adversarial attack methods have been deceived rather easily on deep neural networks (DNNs). In practice, adversarial patches cause misclassification that can be extremely effective. However, many existing adversarial patches are used for
Thi-Thu-Huong Le, Hyoeun Kang, Howon Kim
doaj   +1 more source