Imagen de Portada

Continual Adversarial Defense

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Wang, Qian, Ling, Hefei, Li, Yingwei, Liu, Qihao, Jia, Ruoxi, Yu, Ning
Formato:	Preprint
Publicado:	2023
Materias:	Computer Vision and Pattern Recognition Cryptography and Security Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Let the Noise Speak: Harnessing Noise for a Unified Defense Against Adversarial and Backdoor Attacks
por: Shahriar, Md Hasan, et al.
Publicado: (2024)

Adversarial Defenses via Vector Quantization
por: Dong, Zhiyi, et al.
Publicado: (2023)

Interpretability-Guided Test-Time Adversarial Defense
por: Kulkarni, Akshay, et al.
Publicado: (2024)

Adversarial Sparse Teacher: Defense Against Distillation-Based Model Stealing Attacks Using Adversarial Examples
por: Yilmaz, Eda, et al.
Publicado: (2024)

Meta Invariance Defense Towards Generalizable Robustness to Unknown Adversarial Attacks
por: Zhang, Lei, et al.
Publicado: (2024)

Data-free Defense of Black Box Models Against Adversarial Attacks
por: Nayak, Gaurav Kumar, et al.
Publicado: (2022)

Adversarially Guided Stateful Defense Against Backdoor Attacks in Federated Deep Learning
por: Ali, Hassan, et al.
Publicado: (2024)

Ensemble Adversarial Defense via Integration of Multiple Dispersed Low Curvature Models
por: Zhao, Kaikang, et al.
Publicado: (2024)

Transferable Adversarial Attacks on SAM and Its Downstream Models
por: Xia, Song, et al.
Publicado: (2024)

Evaluating Adversarial Robustness: A Comparison Of FGSM, Carlini-Wagner Attacks, And The Role of Distillation as Defense Mechanism
por: Sarkar, Trilokesh Ranjan, et al.
Publicado: (2024)

Enhancing Adversarial Example Detection Through Model Explanation
por: Ma, Qian, et al.
Publicado: (2025)

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

Detecting Adversarial Data using Perturbation Forgery
por: Wang, Qian, et al.
Publicado: (2024)

DIFFender: Diffusion-Based Adversarial Defense against Patch Attacks
por: Kang, Caixin, et al.
Publicado: (2023)

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

Penny Wise, Pixel Foolish: Bypassing Price Constraints in Multimodal Agents via Visual Adversarial Perturbations
por: Qian, Jiachen, et al.
Publicado: (2026)

Transcending Adversarial Perturbations: Manifold-Aided Adversarial Examples with Legitimate Semantics
por: Li, Shuai, et al.
Publicado: (2024)

Real-world Adversarial Defense against Patch Attacks based on Diffusion Model
por: Wei, Xingxing, et al.
Publicado: (2024)

Learning Differentially Private Diffusion Models via Stochastic Adversarial Distillation
por: Liu, Bochao, et al.
Publicado: (2024)

Struggle with Adversarial Defense? Try Diffusion
por: Li, Yujie, et al.
Publicado: (2024)

AICAttack: Adversarial Image Captioning Attack with Attention-Based Optimization
por: Li, Jiyao, et al.
Publicado: (2024)

Noise-Aware and Dynamically Adaptive Federated Defense Framework for SAR Image Target Recognition
por: Hou, Yuchao, et al.
Publicado: (2025)

Why Does Little Robustness Help? A Further Step Towards Understanding Adversarial Transferability
por: Zhang, Yechao, et al.
Publicado: (2023)

Soften to Defend: Towards Adversarial Robustness via Self-Guided Label Refinement
por: Yu, Daiwei, et al.
Publicado: (2024)

Boosting Adversarial Transferability via Residual Perturbation Attack
por: Peng, Jinjia, et al.
Publicado: (2025)

Adversarial Training against Location-Optimized Adversarial Patches
por: Rao, Sukrut, et al.
Publicado: (2020)

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

PuriDefense: Randomized Local Implicit Adversarial Purification for Defending Black-box Query-based Attacks
por: Guo, Ping, et al.
Publicado: (2024)

Reliable Disentanglement Multi-view Learning Against View Adversarial Attacks
por: Wang, Xuyang, et al.
Publicado: (2025)

UnMarker: A Universal Attack on Defensive Image Watermarking
por: Kassis, Andre, et al.
Publicado: (2024)

MMCert: Provable Defense against Adversarial Attacks to Multi-modal Models
por: Wang, Yanting, et al.
Publicado: (2024)

Adversarial Pruning: A Survey and Benchmark of Pruning Methods for Adversarial Robustness
por: Piras, Giorgio, et al.
Publicado: (2024)

SemiAdv: Query-Efficient Black-Box Adversarial Attack with Unlabeled Images
por: Fan, Mingyuan, et al.
Publicado: (2024)

Transferability Bound Theory: Exploring Relationship between Adversarial Transferability and Flatness
por: Fan, Mingyuan, et al.
Publicado: (2023)

AR-GAN: Generative Adversarial Network-Based Defense Method Against Adversarial Attacks on the Traffic Sign Classification System of Autonomous Vehicles
por: Salek, M Sabbir, et al.
Publicado: (2023)

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

Attack Anything: Blind DNNs via Universal Background Adversarial Attack
por: Lian, Jiawei, et al.
Publicado: (2024)

RPP: A Certified Poisoned-Sample Detection Framework for Backdoor Attacks under Dataset Imbalance
por: Lin, Miao, et al.
Publicado: (2026)

Exploring Adversarial Attacks against Latent Diffusion Model from the Perspective of Adversarial Transferability
por: Chen, Junxi, et al.
Publicado: (2024)

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