Results 51 to 60 of about 5,389,393 (319)
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
doaj +1 more source
CoRR, 2020 Appears in: Advances in Neural Information Processing Systems 33 (NeurIPS 2020)
Avishek Joey Bose +6 more
openaire +3 more sources
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
openaire +2 more sources
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
openaire +2 more sources
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
doaj +1 more source
Adversarial Examples and Metrics
CoRR, 2020 25 pages, 1 figure, under submission, fixe typos from previous ...
Nico Döttling +3 more
openaire +2 more sources
“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
openaire +2 more sources
Self-Supervised Adversarial Example Detection by Disentangled Representation
, 2022 Deep learning models are known to be vulnerable to adversarial examples that are elaborately designed for malicious purposes and are imperceptible to the human perceptual system. Autoencoder, when trained solely over benign examples, has been widely used
Zheng, Xufei +4 more
core +1 more source
A Hybrid Adversarial Attack for Different Application Scenarios
Applied Sciences, 2020 Adversarial attack against natural language has been a hot topic in the field of artificial intelligence security in recent years. It is mainly to study the methods and implementation of generating adversarial examples. The purpose is to better deal with
Xiaohu Du +6 more
doaj +1 more source
Dual-Targeted Textfooler Attack on Text Classification Systems
IEEE Access, 2023 Deep neural networks provide good performance on classification tasks such as those for image, audio, and text classification. However, such neural networks are vulnerable to adversarial examples.
Hyun Kwon
doaj +1 more source