Fine-tuning is Not Fine: Mitigating Backdoor Attacks in GNNs with Limited Clean Data
Fuente:
arXiv
Saved in:
| Main Authors: | Zhang, Jiale, Rao, Bosen, Zhu, Chengcheng, Sun, Xiaobing, Li, Qingming, Hu, Haibo, Luo, Xiapu, Ye, Qingqing, Ji, Shouling |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
"No Matter What You Do": Purifying GNN Models via Backdoor Unlearning
by: Zhang, Jiale, et al.
Published: (2024)
by: Zhang, Jiale, et al.
Published: (2024)
SPA: Towards More Stealth and Persistent Backdoor Attacks in Federated Learning
by: Zhu, Chengcheng, et al.
Published: (2025)
by: Zhu, Chengcheng, et al.
Published: (2025)
Mitigating Fine-tuning based Jailbreak Attack with Backdoor Enhanced Safety Alignment
by: Wang, Jiongxiao, et al.
Published: (2024)
by: Wang, Jiongxiao, et al.
Published: (2024)
Dullahan: Stealthy Backdoor Attack against Without-Label-Sharing Split Learning
by: Pu, Yuwen, et al.
Published: (2024)
by: Pu, Yuwen, et al.
Published: (2024)
Infighting in the Dark: Multi-Label Backdoor Attack in Federated Learning
by: Li, Ye, et al.
Published: (2024)
by: Li, Ye, et al.
Published: (2024)
Backdoor Cleaning without External Guidance in MLLM Fine-tuning
by: Rong, Xuankun, et al.
Published: (2025)
by: Rong, Xuankun, et al.
Published: (2025)
Towards Generalized and Stealthy Watermarking for Generative Code Models
by: Li, Haoxuan, et al.
Published: (2025)
by: Li, Haoxuan, 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)
by: Pu, Yuwen, et al.
Published: (2024)
DMGNN: Detecting and Mitigating Backdoor Attacks in Graph Neural Networks
by: Sui, Hao, et al.
Published: (2024)
by: Sui, Hao, et al.
Published: (2024)
BDFirewall: Towards Effective and Expeditiously Black-Box Backdoor Defense in MLaaS
by: Li, Ye, et al.
Published: (2025)
by: Li, Ye, et al.
Published: (2025)
Data Poisoning Attacks to Local Differential Privacy Protocols for Graphs
by: He, Xi, et al.
Published: (2024)
by: He, Xi, et al.
Published: (2024)
Interactive Trimming against Evasive Online Data Manipulation Attacks: A Game-Theoretic Approach
by: Fu, Yue, et al.
Published: (2024)
by: Fu, Yue, et al.
Published: (2024)
UNIDOOR: A Universal Framework for Action-Level Backdoor Attacks in Deep Reinforcement Learning
by: Ma, Oubo, et al.
Published: (2025)
by: Ma, Oubo, et al.
Published: (2025)
MalModel: Hiding Malicious Payload in Mobile Deep Learning Models with Black-box Backdoor Attack
by: Hua, Jiayi, et al.
Published: (2024)
by: Hua, Jiayi, et al.
Published: (2024)
Watch the Watcher! Backdoor Attacks on Security-Enhancing Diffusion Models
by: Li, Changjiang, et al.
Published: (2024)
by: Li, Changjiang, et al.
Published: (2024)
Attack via Overfitting: 10-shot Benign Fine-tuning to Jailbreak LLMs
by: Xie, Zhixin, et al.
Published: (2025)
by: Xie, Zhixin, et al.
Published: (2025)
Clean-Label Physical Backdoor Attacks with Data Distillation
by: Dao, Thinh, et al.
Published: (2024)
by: Dao, Thinh, et al.
Published: (2024)
CleanGen: Mitigating Backdoor Attacks for Generation Tasks in Large Language Models
by: Li, Yuetai, et al.
Published: (2024)
by: Li, Yuetai, et al.
Published: (2024)
BDPFL: Backdoor Defense for Personalized Federated Learning via Explainable Distillation
by: Zhu, Chengcheng, et al.
Published: (2025)
by: Zhu, Chengcheng, et al.
Published: (2025)
PEFTGuard: Detecting Backdoor Attacks Against Parameter-Efficient Fine-Tuning
by: Sun, Zhen, et al.
Published: (2024)
by: Sun, Zhen, et al.
Published: (2024)
ReCIT: Reconstructing Full Private Data from Gradient in Parameter-Efficient Fine-Tuning of Large Language Models
by: Xie, Jin, et al.
Published: (2025)
by: Xie, Jin, et al.
Published: (2025)
Poison in the Well: Feature Embedding Disruption in Backdoor Attacks
by: Feng, Zhou, et al.
Published: (2025)
by: Feng, Zhou, et al.
Published: (2025)
When Forgetting Triggers Backdoors: A Clean Unlearning Attack
by: Arazzi, Marco, et al.
Published: (2025)
by: Arazzi, Marco, et al.
Published: (2025)
CAMH: Advancing Model Hijacking Attack in Machine Learning
by: He, Xing, et al.
Published: (2024)
by: He, Xing, et al.
Published: (2024)
Privacy for Free: Leveraging Local Differential Privacy Perturbed Data from Multiple Services
by: Du, Rong, et al.
Published: (2025)
by: Du, Rong, et al.
Published: (2025)
Clean-image Backdoor Attacks
by: Rong, Dazhong, et al.
Published: (2024)
by: Rong, Dazhong, et al.
Published: (2024)
TooBadRL: Trigger Optimization to Boost Effectiveness of Backdoor Attacks on Deep Reinforcement Learning
by: Zhang, Mingxuan, et al.
Published: (2025)
by: Zhang, Mingxuan, et al.
Published: (2025)
CBPF: Filtering Poisoned Data Based on Composite Backdoor Attack
by: Xia, Hanfeng, et al.
Published: (2024)
by: Xia, Hanfeng, et al.
Published: (2024)
Membership Inference Attacks and Defenses in Federated Learning: A Survey
by: Bai, Li, et al.
Published: (2024)
by: Bai, Li, et al.
Published: (2024)
Persistent Backdoor Attacks under Continual Fine-Tuning of LLMs
by: Cui, Jing, et al.
Published: (2025)
by: Cui, Jing, et al.
Published: (2025)
Selection-Based Vulnerabilities: Clean-Label Backdoor Attacks in Active Learning
by: Zhi, Yuhan, et al.
Published: (2025)
by: Zhi, Yuhan, et al.
Published: (2025)
Black-box Membership Inference Attacks against Fine-tuned Diffusion Models
by: Pang, Yan, et al.
Published: (2023)
by: Pang, Yan, et al.
Published: (2023)
Mesh Watermark Removal Attack and Mitigation: A Novel Perspective of Function Space
by: Zhu, Xingyu, et al.
Published: (2023)
by: Zhu, Xingyu, et al.
Published: (2023)
Mitigating Backdoor Triggered and Targeted Data Poisoning Attacks in Voice Authentication Systems
by: Mohammadi, Alireza, et al.
Published: (2025)
by: Mohammadi, Alireza, et al.
Published: (2025)
Federated Heavy Hitter Analytics with Local Differential Privacy
by: Zhang, Yuemin, et al.
Published: (2024)
by: Zhang, Yuemin, et al.
Published: (2024)
Modern DDoS Threats and Countermeasures: Insights into Emerging Attacks and Detection Strategies
by: Wang, Jincheng, et al.
Published: (2025)
by: Wang, Jincheng, et al.
Published: (2025)
Detecting Instruction Fine-tuning Attacks using Influence Function
by: Li, Jiawei
Published: (2025)
by: Li, Jiawei
Published: (2025)
How Much Do Code Language Models Remember? An Investigation on Data Extraction Attacks before and after Fine-tuning
by: Salerno, Fabio, et al.
Published: (2025)
by: Salerno, Fabio, et al.
Published: (2025)
Toward Efficient Inference Attacks: Shadow Model Sharing via Mixture-of-Experts
by: Bai, Li, et al.
Published: (2025)
by: Bai, Li, et al.
Published: (2025)
LDPRecover: Recovering Frequencies from Poisoning Attacks against Local Differential Privacy
by: Sun, Xinyue, et al.
Published: (2024)
by: Sun, Xinyue, et al.
Published: (2024)
Similar Items
-
"No Matter What You Do": Purifying GNN Models via Backdoor Unlearning
by: Zhang, Jiale, et al.
Published: (2024) -
SPA: Towards More Stealth and Persistent Backdoor Attacks in Federated Learning
by: Zhu, Chengcheng, et al.
Published: (2025) -
Mitigating Fine-tuning based Jailbreak Attack with Backdoor Enhanced Safety Alignment
by: Wang, Jiongxiao, et al.
Published: (2024) -
Dullahan: Stealthy Backdoor Attack against Without-Label-Sharing Split Learning
by: Pu, Yuwen, et al.
Published: (2024) -
Infighting in the Dark: Multi-Label Backdoor Attack in Federated Learning
by: Li, Ye, et al.
Published: (2024)