Cover Image

Universal Backdoor Attacks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Schneider, Benjamin, Lukas, Nils, Kerschbaum, Florian
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Cryptography and Security Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

IU: Imperceptible Universal Backdoor Attack
by: Lin, Hsin, et al.
Published: (2026)

Backdoor Attack with Sparse and Invisible Trigger
by: Gao, Yinghua, et al.
Published: (2023)

Memory Backdoor Attacks on Neural Networks
by: Luzon, Eden, et al.
Published: (2024)

Invisible Backdoor Attacks on Diffusion Models
by: Li, Sen, et al.
Published: (2024)

Beating Backdoor Attack at Its Own Game
by: Liu, Min, et al.
Published: (2023)

DisDet: Exploring Detectability of Backdoor Attack on Diffusion Models
by: Sui, Yang, et al.
Published: (2024)

VillanDiffusion: A Unified Backdoor Attack Framework for Diffusion Models
by: Chou, Sheng-Yen, et al.
Published: (2023)

Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks
by: Nguyen, Quang H., et al.
Published: (2024)

CorruptEncoder: Data Poisoning based Backdoor Attacks to Contrastive Learning
by: Zhang, Jinghuai, et al.
Published: (2022)

PointBA: Towards Backdoor Attacks in 3D Point Cloud
by: Li, Xinke, et al.
Published: (2021)

Bad-PFL: Exploring Backdoor Attacks against Personalized Federated Learning
by: Fan, Mingyuan, et al.
Published: (2025)

FLARE: Toward Universal Dataset Purification against Backdoor Attacks
by: Hou, Linshan, et al.
Published: (2024)

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

DeepBaR: Fault Backdoor Attack on Deep Neural Network Layers
by: Martínez-Mejía, C. A., et al.
Published: (2024)

Sneaky Spikes: Uncovering Stealthy Backdoor Attacks in Spiking Neural Networks with Neuromorphic Data
by: Abad, Gorka, et al.
Published: (2023)

ToxicTextCLIP: Text-Based Poisoning and Backdoor Attacks on CLIP Pre-training
by: Yao, Xin, et al.
Published: (2025)

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

Not All Prompts Are Secure: A Switchable Backdoor Attack Against Pre-trained Vision Transformers
by: Yang, Sheng, et al.
Published: (2024)

Goal-oriented Backdoor Attack against Vision-Language-Action Models via Physical Objects
by: Zhou, Zirun, et al.
Published: (2025)

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

Under-confidence Backdoors Are Resilient and Stealthy Backdoors
by: Peng, Minlong, et al.
Published: (2022)

Defending Our Privacy With Backdoors
by: Hintersdorf, Dominik, et al.
Published: (2023)

Backdoor Federated Learning by Poisoning Backdoor-Critical Layers
by: Zhuang, Haomin, et al.
Published: (2023)

BadCM: Invisible Backdoor Attack Against Cross-Modal Learning
by: Zhang, Zheng, et al.
Published: (2024)

Backdoor Attacks on Deep Learning Face Detection
by: Roux, Quentin Le, et al.
Published: (2025)

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

Unveiling and Mitigating Backdoor Vulnerabilities based on Unlearning Weight Changes and Backdoor Activeness
by: Lin, Weilin, et al.
Published: (2024)

Sparse and Transferable Universal Singular Vectors Attack
by: Kuvshinova, Kseniia, et al.
Published: (2024)

How to Backdoor Consistency Models?
by: Wang, Chengen, et al.
Published: (2024)

FedDefender: Backdoor Attack Defense in Federated Learning
by: Gill, Waris, et al.
Published: (2023)

Backdooring Outlier Detection Methods: A Novel Attack Approach
by: Taghavi, ZeinabSadat, et al.
Published: (2024)

Leveraging Optimization for Adaptive Attacks on Image Watermarks
by: Lukas, Nils, et al.
Published: (2023)

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

Consistent Attack: Universal Adversarial Perturbation on Embodied Vision Navigation
by: Ying, Chengyang, et al.
Published: (2022)

Mudjacking: Patching Backdoor Vulnerabilities in Foundation Models
by: Liu, Hongbin, et al.
Published: (2024)

Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks
by: Struppek, Lukas, et al.
Published: (2023)

Beyond Traditional Threats: A Persistent Backdoor Attack on Federated Learning
by: Liu, Tao, et al.
Published: (2024)

SoK: On the Survivability of Backdoor Attacks on Unconstrained Face Recognition Systems
by: Roux, Quentin Le, et al.
Published: (2025)

Taught Well Learned Ill: Towards Distillation-conditional Backdoor Attack
by: Chen, Yukun, et al.
Published: (2025)

Long-Tailed Backdoor Attack Using Dynamic Data Augmentation Operations
by: Pang, Lu, et al.
Published: (2024)