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Universal attention guided adversarial defense using feature pyramid and non-local mechanisms [PDF]
Scientific ReportsDeep Neural Networks (DNNs) have been shown to be vulnerable to adversarial examples, significantly hindering the development of deep learning technologies in high-security domains. A key challenge is that current defense methods often lack universality,
Jiawei Zhao +6 more
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Survey of Image Adversarial Example Defense Techniques [PDF]
Jisuanji kexue yu tansuo, 2023 The rapid and extensive growth of artificial intelligence introduces new security challenges. The generation and defense of adversarial examples for deep neural networks is one of the hot spots.
LIU Ruiqi, LI Hu, WANG Dongxia, ZHAO Chongyang, LI Boyu
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Adversarial Sample Defense Method Based on Noise Dissolution [PDF]
Jisuanji gongcheng, 2022 The security problems exposed in the rapid development of the Deep Neural Network(DNN) have gradually attracted our attention.However, since adversarial examples were first defined, many adversarial attacks on DNNs have been proposed, and the complexity ...
YANG Wenxue, WU Fei, GUO Tong, XIAO Limin
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Research Progress of Adversarial Defenses on Graphs
Jisuanji kexue yu tansuo, 2021 Graph neural networks (GNN) have been successfully applied in complex tasks in many fields, but recent studies show that GNN is vulnerable to graph adversarial attacks, leading to severe performance degradation.
LI Penghui, ZHAI Zhengli, FENG Shu
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Survey of Adversarial Attacks and Defense Methods for Deep Learning Model [PDF]
Jisuanji gongcheng, 2021 As an important part of artificial intelligence technology,deep learning is widely used in computer vision,natural language processing and other fields.Although deep learning performs well in tasks such as image classification and target detection,its ...
JIANG Yan, ZHANG Liguo
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Clustering Approach for Detecting Multiple Types of Adversarial Examples
Sensors, 2022 With intentional feature perturbations to a deep learning model, the adversary generates an adversarial example to deceive the deep learning model.
Seok-Hwan Choi +3 more
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Adversarial example defense algorithm for MNIST based on image reconstruction
网络与信息安全学报, 2022 With the popularization of deep learning, more and more attention has been paid to its security issues.The adversarial sample is to add a small disturbance to the original image, which can cause the deep learning model to misclassify the image, which ...
Zhongyuan QIN +3 more
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IEEE Access, 2022 An adversarial example, which is an input instance with small, intentional feature perturbations to machine learning models, represents a concrete problem in Artificial intelligence safety.
Seok-Hwan Choi +3 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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A Defense Method Against FGSM Adversarial Attack [PDF]
Jisuanji gongcheng, 2021 Intelligent ship recognition has been widely used in the military,but it also brings increasingly serious security issues.Even the high performance classification models are still vulnerable to the attacks from adversarial examples.For Fast Gradient Sign
WANG Xiaopeng, LUO Wei, QIN Ke, YANG Jintao, WANG Min
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