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MTD-AD: Moving Target Defense as Adversarial Defense
IEEE Transactions on Dependable and Secure ComputingNetwork Intrusion Detection Systems (NIDSes) are increasingly incorporating Machine Learning (ML) and Deep Learning (DL) algorithms for detecting network intrusions. However, ML/DL algorithms are susceptible to adversarial examples, which can lead to the misclassification of input data.
Ke He +2 more
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Variational Adversarial Defense: A Bayes Perspective for Adversarial Training
IEEE Transactions on Pattern Analysis and Machine IntelligenceVarious methods have been proposed to defend against adversarial attacks. However, there is a lack of enough theoretical guarantee of the performance, thus leading to two problems: First, deficiency of necessary adversarial training samples might attenuate the normal gradient's back-propagation, which leads to overfitting and gradient masking ...
Chenglong Zhao +5 more
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Multi-Scale Defense of Adversarial Images
2019 IEEE International Conference on Image Processing (ICIP), 2019Deep learning has achieved great success in image classification. However, recent researches show that existing deep learning-based classifiers remain weak for recognizing adversarial images. In this paper, an effective multi-scale defense method is proposed to solve the problem.
Jiahuan Ji, Baojiang Zhong, Kai-Kuang Ma
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Adversarial Defense in Aerial Detection
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023Yuwei Chen, Shiyong Chu
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Adversarial anchor-guided feature refinement for adversarial defense
Image and Vision Computing, 2023Hakmin Lee, Yong Man Ro
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A Survey of Adversarial Attack and Defense Methods for Malware Classification in Cyber Security
IEEE Communications Surveys and Tutorials, 2023, , Quan Yu
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Adversarial attack and defense technologies in natural language processing: A survey
Neurocomputing, 2022Shijie Zhou, Wen Huang, Shilin Qiu
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Learning defense transformations for counterattacking adversarial examples
Neural Networks, 2023Mingkui Tan, Jiezhang Cao
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Adversarial Sample Attack and Defense Method for Encrypted Traffic Data
IEEE Transactions on Intelligent Transportation Systems, 2022Zhiguang Qin +2 more
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