Cover Image

VisPoison: An Effective Backdoor Attack Framework for Tabular Data Visualization Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Shuaimin, Zhang, Chen Jason, Chen, Xuanang, Peng, Anni, Wan, Zhuoyue, Song, Yuanfeng, Ni, Shiwen, Yang, Min, Hao, Fei, Wong, Raymond Chi-Wing
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DataVisT5: A Pre-trained Language Model for Jointly Understanding Text and Data Visualization
by: Wan, Zhuoyue, et al.
Published: (2024)

Prompt4Vis: Prompting Large Language Models with Example Mining and Schema Filtering for Tabular Data Visualization
by: Li, Shuaimin, et al.
Published: (2024)

Poisoning-based Backdoor Attacks for Arbitrary Target Label with Positive Triggers
by: Huang, Binxiao, et al.
Published: (2024)

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

Poisoning the Pixels: Revisiting Backdoor Attacks on Semantic Segmentation
by: Zhang, Guangsheng, et al.
Published: (2026)

Towards Stealthy and Effective Backdoor Attacks on Lane Detection: A Naturalistic Data Poisoning Approach
by: Liao, Yifan, et al.
Published: (2025)

OsmT: Bridging OpenStreetMap Queries and Natural Language with Open-source Tag-aware Language Models
by: Wan, Zhuoyue, et al.
Published: (2025)

MultiVis-Agent: A Multi-Agent Framework with Logic Rules for Reliable and Comprehensive Cross-Modal Data Visualization
by: Lu, Jinwei, et al.
Published: (2026)

Activation Gradient based Poisoned Sample Detection Against Backdoor Attacks
by: Yuan, Danni, et al.
Published: (2023)

Backdoor Attacks on Transformers for Tabular Data: An Empirical Study
by: Pleiter, Bart, et al.
Published: (2023)

CBPF: Filtering Poisoned Data Based on Composite Backdoor Attack
by: Xia, Hanfeng, et al.
Published: (2024)

Mitigating Backdoor Triggered and Targeted Data Poisoning Attacks in Voice Authentication Systems
by: Mohammadi, Alireza, et al.
Published: (2025)

Hiding Backdoors within Event Sequence Data via Poisoning Attacks
by: Ermilova, Alina, et al.
Published: (2023)

Poison in the Well: Feature Embedding Disruption in Backdoor Attacks
by: Feng, Zhou, et al.
Published: (2025)

Exposing Vulnerabilities in RL: A Novel Stealthy Backdoor Attack through Reward Poisoning
by: Zhang, Bokang, et al.
Published: (2025)

PoisonCatcher: Revealing and Identifying LDP Poisoning Attacks in IIoT
by: Shuai, Lisha, et al.
Published: (2024)

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

SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents
by: Rathbun, Ethan, et al.
Published: (2024)

Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks
by: Gosch, Lukas, et al.
Published: (2024)

A Proxy Attack-Free Strategy for Practically Improving the Poisoning Efficiency in Backdoor Attacks
by: Li, Ziqiang, et al.
Published: (2023)

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)

Hidden in Plain Sound: Environmental Backdoor Poisoning Attacks on Whisper, and Mitigations
by: Bartolini, Jonatan, et al.
Published: (2024)

CatBack: Universal Backdoor Attacks on Tabular Data via Categorical Encoding
by: Tajalli, Behrad, et al.
Published: (2025)

Effectiveness of Adversarial Benign and Malware Examples in Evasion and Poisoning Attacks
by: Kozák, Matouš, et al.
Published: (2025)

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

Physical Backdoor Attack can Jeopardize Driving with Vision-Large-Language Models
by: Ni, Zhenyang, et al.
Published: (2024)

Unlearning-Enhanced Website Fingerprinting Attack: Against Backdoor Poisoning in Anonymous Networks
by: Yuan, Yali, et al.
Published: (2025)

Checkerboard: A Simple, Effective, Efficient and Learning-free Clean Label Backdoor Attack with Low Poisoning Budget
by: Yang, Yi, et al.
Published: (2026)

SEEP: Training Dynamics Grounds Latent Representation Search for Mitigating Backdoor Poisoning Attacks
by: He, Xuanli, et al.
Published: (2024)

State Backdoor: Towards Stealthy Real-world Poisoning Attack on Vision-Language-Action Model in State Space
by: Guo, Ji, et al.
Published: (2026)

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

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

Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions
by: Cinà, Antonio Emanuele, et al.
Published: (2021)

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

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

Attack by Yourself: Effective and Unnoticeable Multi-Category Graph Backdoor Attacks with Subgraph Triggers Pool
by: Li, Jiangtong, et al.
Published: (2024)

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

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

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

Mellivora Capensis: A Backdoor-Free Training Framework on the Poisoned Dataset without Auxiliary Data
by: Pu, Yuwen, et al.
Published: (2024)