Cover Image

Is the Trigger Essential? A Feature-Based Triggerless Backdoor Attack in Vertical Federated Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Yige, Lou, Yiwei, Wang, Che, Cao, Yongzhi, Wang, Hanpin
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Revisiting Label Inference Attacks in Vertical Federated Learning: Why They Are Vulnerable and How to Defend
by: Liu, Yige, et al.
Published: (2026)

Shortcuts Everywhere and Nowhere: Exploring Multi-Trigger Backdoor Attacks
by: Li, Yige, et al.
Published: (2024)

Cooperative Decentralized Backdoor Attacks on Vertical Federated Learning
by: Lee, Seohyun, et al.
Published: (2025)

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

Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers
by: Liu, Dongyi, et al.
Published: (2025)

On the Out-of-Distribution Backdoor Attack for Federated Learning
by: Xu, Jiahao, et al.
Published: (2025)

Backdoor Attacks in Peer-to-Peer Federated Learning
by: Syros, Georgios, et al.
Published: (2023)

Lurking in the shadows: Unveiling Stealthy Backdoor Attacks against Personalized Federated Learning
by: Lyu, Xiaoting, et al.
Published: (2024)

A Channel-Triggered Backdoor Attack on Wireless Semantic Image Reconstruction
by: Wan, Jialin, et al.
Published: (2025)

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

Invariant Aggregator for Defending against Federated Backdoor Attacks
by: Wang, Xiaoyang, et al.
Published: (2022)

BadFair: Backdoored Fairness Attacks with Group-conditioned Triggers
by: Xue, Jiaqi, et al.
Published: (2024)

How to Defend Against Large-scale Model Poisoning Attacks in Federated Learning: A Vertical Solution
by: Wang, Jinbo, et al.
Published: (2024)

TooBadRL: Trigger Optimization to Boost Effectiveness of Backdoor Attacks on Deep Reinforcement Learning
by: Zhang, Mingxuan, et al.
Published: (2025)

SDBA: A Stealthy and Long-Lasting Durable Backdoor Attack in Federated Learning
by: Choe, Minyeong, et al.
Published: (2024)

Let's Focus: Focused Backdoor Attack against Federated Transfer Learning
by: Arazzi, Marco, et al.
Published: (2024)

Hardware-Triggered Backdoors
by: Möller, Jonas, et al.
Published: (2026)

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

STEP: Detecting Audio Backdoor Attacks via Stability-based Trigger Exposure Profiling
by: Wang, Kun, et al.
Published: (2026)

HashVFL: Defending Against Data Reconstruction Attacks in Vertical Federated Learning
by: Qiu, Pengyu, et al.
Published: (2022)

End-to-End Anti-Backdoor Learning on Images and Time Series
by: Jiang, Yujing, et al.
Published: (2024)

URVFL: Undetectable Data Reconstruction Attack on Vertical Federated Learning
by: Yao, Duanyi, et al.
Published: (2024)

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

Backdoor Attacks on Discrete Graph Diffusion Models
by: Wang, Jiawen, et al.
Published: (2025)

Persistent Backdoor Attacks in Continual Learning
by: Guo, Zhen, et al.
Published: (2024)

Uncovering Attacks and Defenses in Secure Aggregation for Federated Deep Learning
by: Zhang, Yiwei, et al.
Published: (2024)

Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
by: Luo, Xinjian, et al.
Published: (2020)

EmInspector: Combating Backdoor Attacks in Federated Self-Supervised Learning Through Embedding Inspection
by: Qian, Yuwen, et al.
Published: (2024)

KDk: A Defense Mechanism Against Label Inference Attacks in Vertical Federated Learning
by: Arazzi, Marco, et al.
Published: (2024)

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

BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning
by: Jiang, Zhengyuan, et al.
Published: (2024)

FedBAP: Backdoor Defense via Benign Adversarial Perturbation in Federated Learning
by: Yan, Xinhai, et al.
Published: (2025)

Exploiting Layer-Specific Vulnerabilities to Backdoor Attack in Federated Learning
by: Foroughi, Mohammad Hadi, et al.
Published: (2026)

Client-Side Patching against Backdoor Attacks in Federated Learning
by: Molina-Coronado, Borja
Published: (2024)

Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective
by: Zhang, Zhiwei, et al.
Published: (2024)

Watch Out for the Lifespan: Evaluating Backdoor Attacks Against Federated Model Adaptation
by: Vuillod, Bastien, et al.
Published: (2025)

DCInject: Persistent Backdoor Attacks via Frequency Manipulation in Personal Federated Learning
by: Birhan, Nahom, et al.
Published: (2026)

The Art of Deception: Robust Backdoor Attack using Dynamic Stacking of Triggers
by: Mengara, Orson
Published: (2024)

Turn-Based Structural Triggers: Prompt-Free Backdoors in Multi-Turn LLMs
by: Lu, Yiyang, et al.
Published: (2026)

Adversarial Inception Backdoor Attacks against Reinforcement Learning
by: Rathbun, Ethan, et al.
Published: (2024)