Cover Image

Data-Chain Backdoor: Do You Trust Diffusion Models as Generative Data Supplier?

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lu, Junchi, Li, Xinke, Liu, Yuheng, Chen, Qi Alfred
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency
by: Pal, Soumyadeep, et al.
Published: (2024)

Trusted Weights, Treacherous Optimizations? Optimization-Triggered Backdoor Attacks on LLMs
by: Wang, Yifei, et al.
Published: (2026)

Diffusion-Driven Synthetic Tabular Data Generation for Enhanced DoS/DDoS Attack Classification
by: B, Aravind, et al.
Published: (2026)

How to Craft Backdoors with Unlabeled Data Alone?
by: Wang, Yifei, et al.
Published: (2024)

Architectural Backdoors for Within-Batch Data Stealing and Model Inference Manipulation
by: Küchler, Nicolas, et al.
Published: (2025)

TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors
by: Mo, Yichuan, et al.
Published: (2024)

Concealing Backdoor Model Updates in Federated Learning by Trigger-Optimized Data Poisoning
by: Zhang, Yujie, et al.
Published: (2024)

Backdooring Bias ($B^2$) into Stable Diffusion Models
by: Naseh, Ali, et al.
Published: (2024)

Elijah: Eliminating Backdoors Injected in Diffusion Models via Distribution Shift
by: An, Shengwei, et al.
Published: (2023)

Backdoor Graph Condensation
by: Wu, Jiahao, et al.
Published: (2024)

Have You Poisoned My Data? Defending Neural Networks against Data Poisoning
by: De Gaspari, Fabio, et al.
Published: (2024)

PSBD: Prediction Shift Uncertainty Unlocks Backdoor Detection
by: Li, Wei, et al.
Published: (2024)

Heterogeneous Graph Backdoor Attack
by: Chen, Jiawei, et al.
Published: (2025)

Unlearn to Relearn Backdoors: Deferred Backdoor Functionality Attacks on Deep Learning Models
by: Shin, Jeongjin, et al.
Published: (2024)

LoBAM: LoRA-Based Backdoor Attack on Model Merging
by: Yin, Ming, et al.
Published: (2024)

Fast and Lightweight Backdoor Detection via Head Random Probing
by: Yu, Yinbo, et al.
Published: (2026)

Backdoor Attack on Vertical Federated Graph Neural Network Learning
by: Yang, Jirui, et al.
Published: (2024)

Purifying Generative LLMs from Backdoors without Prior Knowledge or Clean Reference
by: Li, Jianwei, et al.
Published: (2026)

Rounding-Guided Backdoor Injection in Deep Learning Model Quantization
by: Chen, Xiangxiang, et al.
Published: (2025)

Pharmacist: Safety Alignment Data Curation for Large Language Models against Harmful Fine-tuning
by: Liu, Guozhi, et al.
Published: (2025)

How to Backdoor the Knowledge Distillation
by: Wu, Chen, et al.
Published: (2025)

Winning the MIDST Challenge: New Membership Inference Attacks on Diffusion Models for Tabular Data Synthesis
by: Wu, Xiaoyu, et al.
Published: (2025)

Flatness-aware Sequential Learning Generates Resilient Backdoors
by: Pham, Hoang, et al.
Published: (2024)

AEGIS: Adversarial Target-Guided Retention-Data-Free Robust Concept Erasure from Diffusion Models
by: Li, Fengpeng, et al.
Published: (2026)

Protecting Copyright of Medical Pre-trained Language Models: Training-Free Backdoor Model Watermarking
by: Kong, Cong, et al.
Published: (2024)

Compromising Embodied Agents with Contextual Backdoor Attacks
by: Liu, Aishan, et al.
Published: (2024)

TrustChain: A Blockchain Framework for Auditing and Verifying Aggregators in Decentralized Federated Learning
by: Hallaji, Ehsan, et al.
Published: (2025)

Your Agent Can Defend Itself against Backdoor Attacks
by: Changjiang, Li, et al.
Published: (2025)

Injecting Universal Jailbreak Backdoors into LLMs in Minutes
by: Chen, Zhuowei, et al.
Published: (2025)

Backdoor Vectors: a Task Arithmetic View on Backdoor Attacks and Defenses
by: Pawlak, Stanisław, et al.
Published: (2025)

Invisible Backdoor Attack Through Singular Value Decomposition
by: Chen, Wenmin, et al.
Published: (2024)

TADP-RME: A Trust-Adaptive Differential Privacy Framework for Enhancing Reliability of Data-Driven Systems
by: Halder, Labani, et al.
Published: (2026)

Rethinking Pruning for Backdoor Mitigation: An Optimization Perspective
by: Li, Nan, et al.
Published: (2024)

Magnitude-based Neuron Pruning for Backdoor Defens
by: Li, Nan, et al.
Published: (2024)

Exploring Query Efficient Data Generation towards Data-free Model Stealing in Hard Label Setting
by: Pei, Gaozheng, et al.
Published: (2024)

BAFFLE: Hiding Backdoors in Offline Reinforcement Learning Datasets
by: Gong, Chen, et al.
Published: (2022)

Mutual Information Guided Backdoor Mitigation for Pre-trained Encoders
by: Han, Tingxu, et al.
Published: (2024)

Graph Neural Backdoor: Fundamentals, Methodologies, Applications, and Future Directions
by: Yang, Xiao, et al.
Published: (2024)

ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks
by: Ren, Zhiyao, et al.
Published: (2025)

Structure-Aware Distributed Backdoor Attacks in Federated Learning
by: Jian, Wang, et al.
Published: (2026)