Enhancing the Transferability of Targeted Attacks with Adversarial Perturbation Transform

Enhancing the Transferability of Targeted Attacks with Adversarial Perturbation Transform

The transferability of adversarial examples has been proven to be a potent tool for successful attacks on target models, even in challenging black-box environments. However, the majority of current research focuses on non-targeted attacks, making it arduous to enhance the transferability of targeted...

Full description

Bibliographic Details
Main Authors:	Zhengjie Deng, Wen Xiao, Xiyan Li, Shuqian He, Yizhen Wang
Format:	Article
Language:	English
Published:	MDPI AG 2023-09-01
Series:	Electronics
Subjects:	adversarial examples transferability perturbation transform targeted attacks
Online Access:	https://www.mdpi.com/2079-9292/12/18/3895

Similar Items

Probabilistic Analysis of Targeted Attacks Using Transform-Domain Adversarial Examples
by: Zakia Yahya, et al.
Published: (2020-01-01)

Maxwell’s Demon in MLP-Mixer: towards transferable adversarial attacks
by: Haoran Lyu, et al.
Published: (2024-03-01)

Adversarial Patch Attacks on Deep-Learning-Based Face Recognition Systems Using Generative Adversarial Networks
by: Ren-Hung Hwang, et al.
Published: (2023-01-01)

DTFA: Adversarial attack with discrete cosine transform noise and target features on deep neural networks
by: Dong Yang, et al.
Published: (2023-04-01)

Crafting Targeted Universal Adversarial Perturbations: Considering Images as Noise
by: Huijiao Wang, et al.
Published: (2023-01-01)

SGMA: a novel adversarial attack approach with improved transferability
by: Peican Zhu, et al.
Published: (2023-04-01)

Advances in Adversarial Attacks and Defenses in Computer Vision: A Survey
by: Naveed Akhtar, et al.
Published: (2021-01-01)

Targeted universal adversarial examples for remote sensing
by: Bai, Tao, et al.
Published: (2023)

Enhancing the robustness of vision transformer defense against adversarial attacks based on squeeze-and-excitation module
by: YouKang Chang, et al.
Published: (2023-01-01)

Adversarial attacks and defenses in deep learning
by: LIU Ximeng, et al.
Published: (2020-10-01)

Boosting Adversarial Attacks with Nadam Optimizer
by: Qikun Zhang, et al.
Published: (2023-03-01)

A Framework for Robust Deep Learning Models Against Adversarial Attacks Based on a Protection Layer Approach
by: Mohammed Nasser Al-Andoli, et al.
Published: (2024-01-01)

Multi-target Category Adversarial Example Generating Algorithm Based on GAN
by: LI Jian, GUO Yan-ming, YU Tian-yuan, WU Yu-lun, WANG Xiang-han, LAO Song-yang
Published: (2022-02-01)

Enhancing the Transferability of Adversarial Examples with Feature Transformation
by: Hao-Qi Xu, et al.
Published: (2022-08-01)

On the Effectiveness of Adversarial Training in Defending against Adversarial Example Attacks for Image Classification
by: Sanglee Park, et al.
Published: (2020-11-01)

Adversarial Deep Learning: A Survey on Adversarial Attacks and Defense Mechanisms on Image Classification
by: Samer Y. Khamaiseh, et al.
Published: (2022-01-01)

A Hybrid Adversarial Attack for Different Application Scenarios
by: Xiaohu Du, et al.
Published: (2020-05-01)

Targeted Universal Adversarial Examples for Remote Sensing
by: Tao Bai, et al.
Published: (2022-11-01)

An Effective Adversarial Attack on Person Re-Identification in Video Surveillance via Dispersion Reduction
by: Yu Zheng, et al.
Published: (2020-01-01)

Adaptive Wiener Filter and Natural Noise to Eliminate Adversarial Perturbation
by: Fei Wu, et al.
Published: (2020-10-01)

Adversarial Attack and Defense Strategies of Speaker Recognition Systems: A Survey
by: Hao Tan, et al.
Published: (2022-07-01)

Adversarial Attack for SAR Target Recognition Based on UNet-Generative Adversarial Network
by: Chuan Du, et al.
Published: (2021-10-01)

Improving the Transferability of Adversarial Examples With a Noise Data Enhancement Framework and Random Erasing
by: Pengfei Xie, et al.
Published: (2021-12-01)

IG-Based Method for Voiceprint Universal Adversarial Perturbation Generation
by: Meng Bi, et al.
Published: (2024-02-01)

Moving target defense against adversarial attacks
by: WANG Bin, et al.
Published: (2021-02-01)

Adversarial Attack and Defense on Deep Neural Network-Based Voice Processing Systems: An Overview
by: Xiaojiao Chen, et al.
Published: (2021-09-01)

DTA: distribution transform-based attack for query-limited scenario
by: Renyang Liu, et al.
Published: (2024-04-01)

Adversarial attacks on deep learning models in smart grids
by: Jingbo Hao, et al.
Published: (2022-05-01)

ARGAN: Adversarially Robust Generative Adversarial Networks for Deep Neural Networks Against Adversarial Examples
by: Seok-Hwan Choi, et al.
Published: (2022-01-01)

Adversarial attack and defense in reinforcement learning-from AI security view
by: Tong Chen, et al.
Published: (2019-03-01)

Targeted Speech Adversarial Example Generation With Generative Adversarial Network
by: Donghua Wang, et al.
Published: (2020-01-01)

A Momentum-Based Local Face Adversarial Example Generation Algorithm
by: Dapeng Lang, et al.
Published: (2022-12-01)

Adversarial Attack and Defense: A Survey
by: Hongshuo Liang, et al.
Published: (2022-04-01)

A Distributed Black-Box Adversarial Attack Based on Multi-Group Particle Swarm Optimization
by: Naufal Suryanto, et al.
Published: (2020-12-01)

Semantic Adversarial Attacks on Face Recognition Through Significant Attributes
by: Yasmeen M. Khedr, et al.
Published: (2023-12-01)

DDSG-GAN: Generative Adversarial Network with Dual Discriminators and Single Generator for Black-Box Attacks
by: Fangwei Wang, et al.
Published: (2023-02-01)

A Two-Stage Generative Adversarial Networks With Semantic Content Constraints for Adversarial Example Generation
by: Jianyi Liu, et al.
Published: (2020-01-01)

AT-BOD: An Adversarial Attack on Fool DNN-Based Blackbox Object Detection Models
by: Ilham A. Elaalami, et al.
Published: (2022-02-01)

Adaptative Perturbation Patterns: Realistic Adversarial Learning for Robust Intrusion Detection
by: João Vitorino, et al.
Published: (2022-03-01)

SSQLi: A Black-Box Adversarial Attack Method for SQL Injection Based on Reinforcement Learning
by: Yuting Guan, et al.
Published: (2023-03-01)