Cover Image

CBPF: Filtering Poisoned Data Based on Composite Backdoor Attack

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xia, Hanfeng, Hong, Haibo, Wang, Ruili
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

BadSkill: Backdoor Attacks on Agent Skills via Model-in-Skill Poisoning
by: Tie, Guiyao, et al.
Published: (2026)

Virus Infection Attack on LLMs: Your Poisoning Can Spread "VIA" Synthetic Data
by: Liang, Zi, et al.
Published: (2025)

Toward Polymorphic Backdoor against Semantic Communication via Intensity-Based Poisoning
by: Yang, Xiao, et al.
Published: (2026)

Defending Against Weight-Poisoning Backdoor Attacks for Parameter-Efficient Fine-Tuning
by: Zhao, Shuai, et al.
Published: (2024)

Clean-Label Physical Backdoor Attacks with Data Distillation
by: Dao, Thinh, et al.
Published: (2024)

The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright Breaches Without Adjusting Finetuning Pipeline
by: Wang, Haonan, et al.
Published: (2024)

From Poisoned to Aware: Fostering Backdoor Self-Awareness in LLMs
by: Shen, Guangyu, et al.
Published: (2025)

Turning Generative Models Degenerate: The Power of Data Poisoning Attacks
by: Jiang, Shuli, et al.
Published: (2024)

When and Where do Data Poisons Attack Textual Inversion?
by: Styborski, Jeremy, et al.
Published: (2025)

A Set of Generalized Components to Achieve Effective Poison-only Clean-label Backdoor Attacks with Collaborative Sample Selection and Triggers
by: Wu, Zhixiao, et al.
Published: (2025)

DeBackdoor: A Deductive Framework for Detecting Backdoor Attacks on Deep Models with Limited Data
by: Popovic, Dorde, et al.
Published: (2025)

Joint-GCG: Unified Gradient-Based Poisoning Attacks on Retrieval-Augmented Generation Systems
by: Wang, Haowei, et al.
Published: (2025)

Precision Guided Approach to Mitigate Data Poisoning Attacks in Federated Learning
by: Kumar, K Naveen, et al.
Published: (2024)

Vulnerabilities in AI Code Generators: Exploring Targeted Data Poisoning Attacks
by: Cotroneo, Domenico, et al.
Published: (2023)

Selection-Based Vulnerabilities: Clean-Label Backdoor Attacks in Active Learning
by: Zhi, Yuhan, et al.
Published: (2025)

AutoBackdoor: Automating Backdoor Attacks via LLM Agents
by: Li, Yige, et al.
Published: (2025)

LoopTrap: Termination Poisoning Attacks on LLM Agents
by: Xu, Huiyu, et al.
Published: (2026)

Impart: An Imperceptible and Effective Label-Specific Backdoor Attack
by: Zhao, Jingke, et al.
Published: (2024)

Backdoor Attack with Invisible Triggers Based on Model Architecture Modification
by: Ma, Yuan, et al.
Published: (2024)

SkillTrojan: Backdoor Attacks on Skill-Based Agent Systems
by: Feng, Yunhao, et al.
Published: (2026)

When Backdoors Speak: Understanding LLM Backdoor Attacks Through Model-Generated Explanations
by: Ge, Huaizhi, et al.
Published: (2024)

DFB: A Data-Free, Low-Budget, and High-Efficacy Clean-Label Backdoor Attack
by: Ma, Binhao, et al.
Published: (2023)

Revisiting Training-Inference Trigger Intensity in Backdoor Attacks
by: Lin, Chenhao, et al.
Published: (2025)

Poison Once, Exploit Forever: Environment-Injected Memory Poisoning Attacks on Web Agents
by: Zou, Wei, et al.
Published: (2026)

Poison Once, Control Anywhere: Clean-Text Visual Backdoors in VLM-based Mobile Agents
by: Wang, Xuan, et al.
Published: (2025)

PIDP-Attack: Combining Prompt Injection with Database Poisoning Attacks on Retrieval-Augmented Generation Systems
by: Wang, Haozhen, et al.
Published: (2026)

Flashy Backdoor: Real-world Environment Backdoor Attack on SNNs with DVS Cameras
by: Riaño, Roberto, et al.
Published: (2024)

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

Knowledge Poisoning Attacks on Medical Multi-Modal Retrieval-Augmented Generation
by: Yang, Peiru, et al.
Published: (2026)

The Ripple Effect: On Unforeseen Complications of Backdoor Attacks
by: Zhang, Rui, et al.
Published: (2025)

CL-Attack: Textual Backdoor Attacks via Cross-Lingual Triggers
by: Zheng, Jingyi, et al.
Published: (2024)

Injection, Attack and Erasure: Revocable Backdoor Attacks via Machine Unlearning
by: Song, Baogang, et al.
Published: (2025)

P2P: A Poison-to-Poison Remedy for Reliable Backdoor Defense in LLMs
by: Zhao, Shuai, et al.
Published: (2025)

Class-Conditional Neural Polarizer: A Lightweight and Effective Backdoor Defense by Purifying Poisoned Features
by: Zhu, Mingli, et al.
Published: (2025)

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

Robustness Analysis of Machine Learning Models for IoT Intrusion Detection Under Data Poisoning Attacks
by: Wulnye, Fortunatus Aabangbio, et al.
Published: (2026)

Chain-of-Scrutiny: Detecting Backdoor Attacks for Large Language Models
by: Li, Xi, et al.
Published: (2024)

Stealthy Backdoor Attack to Real-world Models in Android Apps
by: Wei, Jiali, et al.
Published: (2025)

One Shot Dominance: Knowledge Poisoning Attack on Retrieval-Augmented Generation Systems
by: Chang, Zhiyuan, et al.
Published: (2025)

Enhancing All-to-X Backdoor Attacks with Optimized Target Class Mapping
by: Wang, Lei, et al.
Published: (2025)