Cover Image

Improving Integrated Gradient-based Transferable Adversarial Examples by Refining the Integration Path

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ren, Yuchen, Zhao, Zhengyu, Lin, Chenhao, Yang, Bo, Zhou, Lu, Liu, Zhe, Shen, Chao
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security Computer Vision and Pattern Recognition Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Improving Adversarial Transferability on Vision Transformers via Forward Propagation Refinement
by: Ren, Yuchen, et al.
Published: (2025)

Prediction Inconsistency Helps Achieve Generalizable Detection of Adversarial Examples
by: Han, Sicong, et al.
Published: (2025)

Physical 3D Adversarial Attacks against Monocular Depth Estimation in Autonomous Driving
by: Zheng, Junhao, et al.
Published: (2024)

Quantization Aware Attack: Enhancing Transferable Adversarial Attacks by Model Quantization
by: Yang, Yulong, et al.
Published: (2023)

A Survey on Adversarial Machine Learning for Code Data: Realistic Threats, Countermeasures, and Interpretations
by: Yang, Yulong, et al.
Published: (2024)

Improving Transferability of Adversarial Examples via Bayesian Attacks
by: Li, Qizhang, et al.
Published: (2023)

Revisiting Adversarial Patch Defenses on Object Detectors: Unified Evaluation, Large-Scale Dataset, and New Insights
by: Zheng, Junhao, et al.
Published: (2025)

Privacy on the Fly: A Predictive Adversarial Transformation Network for Mobile Sensor Data
by: Song, Tianle, et al.
Published: (2025)

Improving Adversarial Transferability with Neighbourhood Gradient Information
by: Guo, Haijing, et al.
Published: (2024)

Transferable Adversarial Examples with Bayes Approach
by: Fan, Mingyuan, et al.
Published: (2022)

Robustness Over Time: Understanding Adversarial Examples' Effectiveness on Longitudinal Versions of Large Language Models
by: Liu, Yugeng, et al.
Published: (2023)

Defensive Adversarial CAPTCHA: A Semantics-Driven Framework for Natural Adversarial Example Generation
by: Du, Xia, et al.
Published: (2025)

Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation
by: Yu, Yi, et al.
Published: (2025)

TwoHamsters: Benchmarking Multi-Concept Compositional Unsafety in Text-to-Image Models
by: Zhang, Chaoshuo, et al.
Published: (2026)

Adversarial 3D Virtual Patches using Integrated Gradients
by: You, Chengzeng, et al.
Published: (2024)

AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples
by: Cinà, Antonio Emanuele, et al.
Published: (2024)

Revisiting Transferable Adversarial Images: Systemization, Evaluation, and New Insights
by: Zhao, Zhengyu, et al.
Published: (2023)

Generalizable Targeted Data Poisoning against Varying Physical Objects
by: Chen, Zhizhen, et al.
Published: (2024)

Systematic Categorization, Construction and Evaluation of New Attacks against Multi-modal Mobile GUI Agents
by: Yang, Yulong, et al.
Published: (2024)

Boosting Adversarial Transferability with Spatial Adversarial Alignment
by: Chen, Zhaoyu, et al.
Published: (2025)

$σ$-zero: Gradient-based Optimization of $\ell_0$-norm Adversarial Examples
by: Cinà, Antonio Emanuele, et al.
Published: (2024)

Adversarial Example Soups: Improving Transferability and Stealthiness for Free
by: Yang, Bo, et al.
Published: (2024)

Revisiting Training-Inference Trigger Intensity in Backdoor Attacks
by: Lin, Chenhao, et al.
Published: (2025)

AED-PADA:Improving Generalizability of Adversarial Example Detection via Principal Adversarial Domain Adaptation
by: Peng, Heqi, et al.
Published: (2024)

Transferability Ranking of Adversarial Examples
by: Levy, Mosh, et al.
Published: (2022)

Adversarial Examples are Misaligned in Diffusion Model Manifolds
by: Lorenz, Peter, et al.
Published: (2024)

SlowPerception: Physical-World Latency Attack against Visual Perception in Autonomous Driving
by: Ma, Chen, et al.
Published: (2024)

Adversarial Attacks of Vision Tasks in the Past 10 Years: A Survey
by: Zhang, Chiyu, et al.
Published: (2024)

Improving Sustainability of Adversarial Examples in Class-Incremental Learning
by: Liu, Taifeng, et al.
Published: (2025)

LESSON: Multi-Label Adversarial False Data Injection Attack for Deep Learning Locational Detection
by: Tian, Jiwei, et al.
Published: (2024)

Minimal Cascade Gradient Smoothing for Fast Transferable Preemptive Adversarial Defense
by: Wang, Hanrui, et al.
Published: (2024)

TriQDef: Disrupting Semantic and Gradient Alignment to Prevent Adversarial Patch Transferability in Quantized Neural Networks
by: Guesmi, Amira, et al.
Published: (2025)

Generating Image Adversarial Examples by Embedding Digital Watermarks
by: Xiang, Yuexin, et al.
Published: (2020)

Natias: Neuron Attribution based Transferable Image Adversarial Steganography
by: Fan, Zexin, et al.
Published: (2024)

Time Traveling to Defend Against Adversarial Example Attacks in Image Classification
by: Etim, Anthony, et al.
Published: (2024)

IrisFP: Adversarial-Example-based Model Fingerprinting with Enhanced Uniqueness and Robustness
by: Geng, Ziye, et al.
Published: (2026)

DP-TRAE: A Dual-Phase Merging Transferable Reversible Adversarial Example for Image Privacy Protection
by: Du, Xia, et al.
Published: (2025)

A Random Ensemble of Encrypted models for Enhancing Robustness against Adversarial Examples
by: Iijima, Ryota, et al.
Published: (2024)

DiffProtect: Generate Adversarial Examples with Diffusion Models for Facial Privacy Protection
by: Liu, Jiang, et al.
Published: (2023)

ViTGuard: Attention-aware Detection against Adversarial Examples for Vision Transformer
by: Sun, Shihua, et al.
Published: (2024)