D-BADGE: Decision-Based Adversarial Batch Attack With Directional Gradient Estimation

D-BADGE: Decision-Based Adversarial Batch Attack With Directional Gradient Estimation

The susceptibility of deep neural networks (DNNs) to adversarial examples has prompted an increase in the deployment of adversarial attacks. Image-agnostic universal adversarial perturbations (UAPs) are much more threatening, but many limitations exist to implementing UAPs in real-world scenarios wh...

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Bibliographic Details
Main Authors: Geunhyeok Yu, Minwoo Jeon, Hyoseok Hwang
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Deep neural networks
universal decision-based adversarial attack
image classification
representation learning
vulnerability
zeroth-order optimization
Online Access:https://ieeexplore.ieee.org/document/10542123/
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