Cover Image

Bad-PFL: Exploring Backdoor Attacks against Personalized Federated Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Fan, Mingyuan, Hu, Zhanyi, Wang, Fuyi, Chen, Cen
Format:	Preprint
Published:	2025
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

Boosting Gradient Leakage Attacks: Data Reconstruction in Realistic FL Settings
by: Fan, Mingyuan, et al.
Published: (2025)

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

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

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

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

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

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

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

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

Universal Backdoor Attacks
by: Schneider, Benjamin, et al.
Published: (2023)

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

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)

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

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

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)

BadViM: Backdoor Attack against Vision Mamba
by: Wu, Yinghao, et al.
Published: (2025)

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

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

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

BadDet+: Robust Backdoor Attacks for Object Detection
by: Dunnett, Kealan, et al.
Published: (2026)

Non-Cooperative Backdoor Attacks in Federated Learning: A New Threat Landscape
by: Nguyen, Tuan, et al.
Published: (2024)

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

FedBlock: A Blockchain Approach to Federated Learning against Backdoor Attacks
by: Nguyen, Duong H., et al.
Published: (2024)

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

BadBone: Backdoor Attacks Against Backbone Models in Visual Prompt Learning
by: Yang, Ziqing, et al.
Published: (2026)

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

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

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

Refiner: Data Refining against Gradient Leakage Attacks in Federated Learning
by: Fan, Mingyuan, et al.
Published: (2022)

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

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

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

On the Trustworthiness Landscape of State-of-the-art Generative Models: A Survey and Outlook
by: Fan, Mingyuan, et al.
Published: (2023)

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

What Does the Server See? Understanding Privacy Leakage from Large Language Models in Split Inference
by: Fan, Mingyuan, et al.
Published: (2026)

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

PADetBench: Towards Benchmarking Physical Attacks against Object Detection
by: Lian, Jiawei, 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)