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Robust Adversarial Example Detection Algorithm Based on High-Level Feature Differences [PDF]
SensorsThe threat posed by adversarial examples (AEs) to deep learning applications has garnered significant attention from the academic community. In response, various defense strategies have been proposed, including adversarial example detection.
Hua Mu +4 more
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Adversarial example defense based on image reconstruction [PDF]
PeerJ Computer Science, 2021 The rapid development of deep neural networks (DNN) has promoted the widespread application of image recognition, natural language processing, and autonomous driving.
Yu(AUST) Zhang +3 more
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Applied Sciences, 2020 State-of-the-art neural network models are actively used in various fields, but it is well-known that they are vulnerable to adversarial example attacks.
Sanglee Park, Jungmin So
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A Cascade Model-Aware Generative Adversarial Example Detection Method
Tsinghua Science and Technology, 2021 Deep Neural Networks (DNNs) are demonstrated to be vulnerable to adversarial examples, which are elaborately crafted to fool learning models. Since the accuracy and robustness of DNNs are at odds for the adversarial training method, the adversarial ...
Keji Han, Yun Li, Bin Xia
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A Novel Adversarial Example Detection Method Based on Frequency Domain Reconstruction for Image Sensors [PDF]
SensorsConvolutional neural networks (CNNs) have been extensively used in numerous remote sensing image detection tasks owing to their exceptional performance.
Shuaina Huang, Zhiyong Zhang, Bin Song
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Multi-Targeted Adversarial Example in Evasion Attack on Deep Neural Network
IEEE Access, 2018 Deep neural networks (DNNs) are widely used for image recognition, speech recognition, pattern analysis, and intrusion detection. Recently, the adversarial example attack, in which the input data are only slightly modified, although not an issue for ...
Hyun Kwon +4 more
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A Robust Adversarial Example Attack Based on Video Augmentation
Applied Sciences, 2023 Despite the success of learning-based systems, recent studies have highlighted video adversarial examples as a ubiquitous threat to state-of-the-art video classification systems.
Mingyong Yin +3 more
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DroidEnemy: Battling adversarial example attacks for Android malware detection
Digital Communications and Networks, 2022 In recent years, we have witnessed a surge in mobile devices such as smartphones, tablets, smart watches, etc., most of which are based on the Android operating system. However, because these Android-based mobile devices are becoming increasingly popular,
Neha Bala +5 more
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Recovery of Adversarial Examples Based on SmsGAN [PDF]
Zhengzhou Daxue xuebao. Gongxue ban, 2021 Due to adversarial examples′ serious interference to the detection models based on deep learning, a recovery method of adversarial examples based on stochastic multihlter statistical generative adversarial network (SmsGAN) was proposed in this work.
ZHAO Junjie, WANG Jinwei
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Natural Adversarial Examples [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 We introduce two challenging datasets that reliably cause machine learning model performance to substantially degrade. The datasets are collected with a simple adversarial filtration technique to create datasets with limited spurious cues. Our datasets' real-world, unmodified examples transfer to various unseen models reliably, demonstrating that ...
Dan Hendrycks +4 more
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