Results 21 to 30 of about 27,717 (260)
Adversarial Examples Detection Method Based on Image Denoising and Compression [PDF]
Jisuanji gongcheng, 2023 Numerous deep learning achievements in the field of computer vision have been widely applied in real life. However, adversarial examples can lead to false positives in deep learning models with high confidence, resulting in serious security consequences.
Feiyu WANG, Fan ZHANG, Jiayu DU, Hongle LEI, Xiaofeng QI
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CoRR, 2020 Appears in: Advances in Neural Information Processing Systems 33 (NeurIPS 2020)
Avishek Joey Bose +6 more
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Adversarial Attack and Defense on Deep Neural Network-Based Voice Processing Systems: An Overview
Applied Sciences, 2021 Voice Processing Systems (VPSes), now widely deployed, have become deeply involved in people’s daily lives, helping drive the car, unlock the smartphone, make online purchases, etc.
Xiaojiao Chen, Sheng Li, Hao Huang
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Adversarial Examples for Good: Adversarial Examples Guided Imbalanced Learning
2022 IEEE International Conference on Image Processing (ICIP), 2022 Appeared in ICIP ...
Jie Zhang 0081 +3 more
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Multi-target Category Adversarial Example Generating Algorithm Based on GAN [PDF]
Jisuanji kexue, 2022 Although deep neural networks perform well in many areas,research shows that deep neural networks are vulnerable to attacks from adversarial examples.There are many algorithms for attacking neural networks,but the attack speed of most attack algorithms ...
LI Jian, GUO Yan-ming, YU Tian-yuan, WU Yu-lun, WANG Xiang-han, LAO Song-yang
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Targeted Speech Adversarial Example Generation With Generative Adversarial Network
IEEE Access, 2020 Although neural network-based speech recognition models have enjoyed significant success in many acoustic systems, they are susceptible to be attacked by the adversarial examples.
Donghua Wang +4 more
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Perceptually Similar Image Classification Adversarial Example Generation Model
Jisuanji kexue yu tansuo, 2020 The existing generator-based adversarial example generation model can effectively reduce the construction time of an adversarial example compared to the algorithms based on iterative original image modification, but the obvious differences between ...
LI Junjie, WANG Qian
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Generating Adversarial Examples with Adversarial Networks [PDF]
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018 Deep neural networks (DNNs) have been found to be vulnerable to adversarial examples resulting from adding small-magnitude perturbations to inputs. Such adversarial examples can mislead DNNs to produce adversary-selected results. Different attack strategies have been proposed to generate adversarial examples, but how to produce them with high ...
Chaowei Xiao +5 more
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“Adversarial Examples” for Proof-of-Learning
2022 IEEE Symposium on Security and Privacy (SP), 2022 To appear in the 43rd IEEE Symposium on Security and ...
Rui Zhang 0118 +5 more
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Unrestricted Adversarial Examples
CoRR, 2018 We introduce a two-player contest for evaluating the safety and robustness of machine learning systems, with a large prize pool. Unlike most prior work in ML robustness, which studies norm-constrained adversaries, we shift our focus to unconstrained adversaries.
Tom B. Brown +5 more
openaire +2 more sources