Black-box Bayesian adversarial attack with transferable priors

Shudong Zhang; Haichang Gao; Chao Shu; Xiwen Cao; Yunyi Zhou; Jianping He

doi:10.1007/s10994-022-06251-3

ScienceGate Book Chapters

JOURNAL ARTICLE

Black-box Bayesian adversarial attack with transferable priors

Shudong Zhang Haichang Gao Chao Shu Xiwen Cao Yunyi Zhou Jianping He

Year: 2022 Journal: Machine Learning Vol: 113 (4)Pages: 1511-1528 Publisher: Springer Science+Business Media

DOI: 10.1007/s10994-022-06251-3

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Bayesian optimization Adversarial system MNIST database Prior probability Bayesian probability Black box Artificial intelligence Machine learning Classifier (UML) Artificial neural network

Metrics

Cited By

0.98

FWCI (Field Weighted Citation Impact)

Refs

0.74

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Adversarial Robustness in Machine Learning

Physical Sciences → Computer Science → Artificial Intelligence

Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Black-box Bayesian adversarial attack with transferable priors

Metrics

Citation History

Topics

Related Documents

Boosting Decision-Based Black-Box Adversarial Attack with Gradient Priors

Transferable Black-Box Attack Against Face Recognition With Spatial Mutable Adversarial Patch

A Data-free Black-box Attack for Generating Transferable Adversarial Examples

Simulator Attack+ for Black-Box Adversarial Attack

Fabricate-Vanish: An Effective And Transferable Black-Box Adversarial Attack Incorporating Feature Distortion