Results 1 to 10 of about 26,718 (222)

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
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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

Double adversarial attack against license plate recognition system

网络与信息安全学报, 2023
Recent studies have revealed that deep neural networks (DNN) used in artificial intelligence systems are highly vulnerable to adversarial sample-based attacks.To address this issue, a dual adversarial attack method was proposed for license plate ...
Xianyi CHEN, Jun GU1, Kai YAN, Dong JIANG, Linfeng XU, Zhangjie FU
doaj   +3 more sources

Bilateral Adversarial Patch Generating Network for the Object Tracking Algorithm

Remote Sensing, 2023
Deep learning-based algorithms for single object tracking (SOT) have shown impressive performance but remain susceptible to adversarial patch attacks. However, existing adversarial patch generation methods primarily focus on generating patches within the
Jarhinbek Rasol, Yuelei Xu, Zhaoxiang Zhang, Chengyang Tao, Tian Hui   +4 more
doaj   +1 more source

Extended Spatially Localized Perturbation GAN (eSLP-GAN) for Robust Adversarial Camouflage Patches

Sensors, 2021
Deep neural networks (DNNs), especially those used in computer vision, are highly vulnerable to adversarial attacks, such as adversarial perturbations and adversarial patches. Adversarial patches, often considered more appropriate for a real-world attack,
Yongsu Kim, Hyoeun Kang, Naufal Suryanto, Harashta Tatimma Larasati, Afifatul Mukaroh, Howon Kim   +5 more
doaj   +1 more source

Defense against Adversarial Patch Attacks for Aerial Image Semantic Segmentation by Robust Feature Extraction

Remote Sensing, 2023
Deep learning (DL) models have recently been widely used in UAV aerial image semantic segmentation tasks and have achieved excellent performance. However, DL models are vulnerable to adversarial examples, which bring significant security risks to safety ...
Zhen Wang, Buhong Wang, Chuanlei Zhang, Yaohui Liu   +3 more
doaj   +1 more source

Adversarial Patch Attacks on Deep-Learning-Based Face Recognition Systems Using Generative Adversarial Networks

Sensors, 2023
Deep learning technology has developed rapidly in recent years and has been successfully applied in many fields, including face recognition. Face recognition is used in many scenarios nowadays, including security control systems, access control ...
Ren-Hung Hwang, Jia-You Lin, Sun-Ying Hsieh, Hsuan-Yu Lin, Chia-Liang Lin   +4 more
doaj   +1 more source