Results 21 to 30 of about 5,384 (200)
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
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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 +4 more
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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 +5 more
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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 +3 more
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Adversarial YOLO: Defense Human Detection Patch Attacks via Detecting Adversarial Patches
CoRR, 2021 9 pages, 7 ...
Nan Ji +4 more
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TPatch: A Triggered Physical Adversarial Patch
CoRR, 2023 Appeared in 32nd USENIX Security Symposium (USENIX Security 23)
Wenjun Zhu +4 more
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Adversarial Training Against Location-Optimized Adversarial Patches [PDF]
, 2020 20 pages, 6 tables, 4 figures, 2 algorithms, European Conference on Computer Vision Workshops ...
Sukrut Rao, David Stutz, Bernt Schiele
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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 +4 more
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Certified Defenses for Adversarial Patches
CoRR, 2020 International Conference on Learning Representations, ICLR ...
Chiang, Ping-yeh +5 more
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Generating Visually Realistic Adversarial Patch
CoRR, 2023 Deep neural networks (DNNs) are vulnerable to various types of adversarial examples, bringing huge threats to security-critical applications. Among these, adversarial patches have drawn increasing attention due to their good applicability to fool DNNs in the physical world.
Xiaosen Wang, Kunyu Wang
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