Cover Image

Leveraging Information Consistency in Frequency and Spatial Domain for Adversarial Attacks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Jin, Zhibo, Zhang, Jiayu, Zhu, Zhiyu, Wang, Xinyi, Huang, Yiyun, Chen, Huaming
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PAR-AdvGAN: Improving Adversarial Attack Capability with Progressive Auto-Regression AdvGAN
by: Zhang, Jiayu, et al.
Published: (2025)

Enhancing Model Interpretability with Local Attribution over Global Exploration
by: Zhu, Zhiyu, et al.
Published: (2024)

DMS: Addressing Information Loss with More Steps for Pragmatic Adversarial Attacks
by: Zhu, Zhiyu, et al.
Published: (2024)

Benchmarking Transferable Adversarial Attacks
by: Jin, Zhibo, et al.
Published: (2024)

ABE: A Unified Framework for Robust and Faithful Attribution-Based Explainability
by: Zhu, Zhiyu, et al.
Published: (2025)

Attribution for Enhanced Explanation with Transferable Adversarial eXploration
by: Zhu, Zhiyu, et al.
Published: (2024)

Enhancing Adversarial Attacks via Parameter Adaptive Adversarial Attack
by: Jin, Zhibo, et al.
Published: (2024)

Enhancing Transferability of Adversarial Attacks with GE-AdvGAN+: A Comprehensive Framework for Gradient Editing
by: Jin, Zhibo, et al.
Published: (2024)

Frequency-Domain Regularized Adversarial Alignment for Transferable Attacks against Closed-Source MLLMs
by: Yuan, Leitao, et al.
Published: (2026)

Revisiting Backdoor Attacks on Time Series Classification in the Frequency Domain
by: Huang, Yuanmin, et al.
Published: (2025)

Beyond Noisy-TVs: Noise-Robust Exploration Via Learning Progress Monitoring
by: Hou, Zhibo, et al.
Published: (2025)

FACL-Attack: Frequency-Aware Contrastive Learning for Transferable Adversarial Attacks
by: Yang, Hunmin, et al.
Published: (2024)

Optimal Look-back Horizon for Time Series Forecasting in Federated Learning
by: Tang, Dahao, et al.
Published: (2025)

Fair Federated Learning under Domain Skew with Local Consistency and Domain Diversity
by: Chen, Yuhang, et al.
Published: (2024)

Fast-Slow Co-advancing Optimizer: Toward Harmonious Adversarial Training of GAN
by: Wang, Lin, et al.
Published: (2025)

MF-CLIP: Leveraging CLIP as Surrogate Models for No-box Adversarial Attacks
by: Zhang, Jiaming, et al.
Published: (2023)

Conflict-Aware Adversarial Training
by: Xue, Zhiyu, et al.
Published: (2024)

Fast Adversarial Training against Sparse Attacks Requires Loss Smoothing
by: Zhong, Xuyang, et al.
Published: (2025)

Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why?
by: Huang, Jin, et al.
Published: (2023)

Direct Routing Gradient (DRGrad): A Personalized Information Surgery for Multi-Task Learning (MTL) Recommendations
by: Liu, Yuguang, et al.
Published: (2025)

Towards Interpretable Adversarial Examples via Sparse Adversarial Attack
by: Lin, Fudong, et al.
Published: (2025)

Frequency maps reveal the correlation between Adversarial Attacks and Implicit Bias
by: Basile, Lorenzo, et al.
Published: (2023)

Domain Adversarial Active Learning for Domain Generalization Classification
by: Chen, Jianting, et al.
Published: (2024)

Rethinking Adversarial Attacks in Reinforcement Learning from Policy Distribution Perspective
by: Duan, Tianyang, et al.
Published: (2025)

What You See Is Not Always What You Get: Evaluating GPT's Comprehension of Source Code
by: Wen, Jiawen, et al.
Published: (2024)

Adversarial Attacks Leverage Interference Between Features in Superposition
by: Stevinson, Edward, et al.
Published: (2025)

Understanding Model Ensemble in Transferable Adversarial Attack
by: Yao, Wei, et al.
Published: (2024)

GuardFed: A Trustworthy Federated Learning Framework Against Dual-Facet Attacks
by: Li, Yanli, et al.
Published: (2025)

Adversarial Attacks on Hyperbolic Networks
by: van Spengler, Max, et al.
Published: (2024)

AnyAttack: Towards Large-scale Self-supervised Adversarial Attacks on Vision-language Models
by: Zhang, Jiaming, et al.
Published: (2024)

Feature-Selective Representation Misdirection for Machine Unlearning
by: Chen, Taozhao, et al.
Published: (2025)

EVGeoQA: Benchmarking LLMs on Dynamic, Multi-Objective Geo-Spatial Exploration
by: Wu, Jianfei, et al.
Published: (2026)

Harmonizing Intra-coherence and Inter-divergence in Ensemble Attacks for Adversarial Transferability
by: Ma, Zhaoyang, et al.
Published: (2025)

FreDF: Learning to Forecast in the Frequency Domain
by: Wang, Hao, et al.
Published: (2024)

Adversarial Preference Learning for Robust LLM Alignment
by: Wang, Yuanfu, et al.
Published: (2025)

Rethinking the Intermediate Features in Adversarial Attacks: Misleading Robotic Models via Adversarial Distillation
by: Zhao, Ke, et al.
Published: (2024)

D-FaST: Cognitive Signal Decoding with Disentangled Frequency-Spatial-Temporal Attention
by: Chen, Weiguo, et al.
Published: (2024)

Towards a Novel Perspective on Adversarial Examples Driven by Frequency
by: Zhang, Zhun, et al.
Published: (2024)

FedProphet: Memory-Efficient Federated Adversarial Training via Robust and Consistent Cascade Learning
by: Tang, Minxue, et al.
Published: (2024)

How Worst-Case Are Adversarial Attacks? Linking Adversarial and Perturbation Robustness
by: Rossolini, Giulio
Published: (2026)