Sybil-based Virtual Data Poisoning Attacks in Federated Learning
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | Zhu, Changxun, Wu, Qilong, Lyu, Lingjuan, Xue, Shibei |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Byzantine-Robust Federated Learning: An Overview With Focus on Developing Sybil-based Attacks to Backdoor Augmented Secure Aggregation Protocols
par: Deshmukh, Atharv
Publié: (2024)
par: Deshmukh, Atharv
Publié: (2024)
GShield: Mitigating Poisoning Attacks in Federated Learning
par: M., Sameera K., et autres
Publié: (2025)
par: M., Sameera K., et autres
Publié: (2025)
Provable Watermarking for Data Poisoning Attacks
par: Zhu, Yifan, et autres
Publié: (2025)
par: Zhu, Yifan, et autres
Publié: (2025)
Local Environment Poisoning Attacks on Federated Reinforcement Learning
par: Ma, Evelyn, et autres
Publié: (2023)
par: Ma, Evelyn, et autres
Publié: (2023)
Defending Against Sophisticated Poisoning Attacks with RL-based Aggregation in Federated Learning
par: Wang, Yujing, et autres
Publié: (2024)
par: Wang, Yujing, et autres
Publié: (2024)
A Data-Driven Defense against Edge-case Model Poisoning Attacks on Federated Learning
par: Purohit, Kiran, et autres
Publié: (2023)
par: Purohit, Kiran, et autres
Publié: (2023)
FedRecAttack: Model Poisoning Attack to Federated Recommendation
par: Rong, Dazhong, et autres
Publié: (2022)
par: Rong, Dazhong, et autres
Publié: (2022)
Partner in Crime: Boosting Targeted Poisoning Attacks against Federated Learning
par: Sun, Shihua, et autres
Publié: (2024)
par: Sun, Shihua, et autres
Publié: (2024)
Towards Efficient and Certified Recovery from Poisoning Attacks in Federated Learning
par: Jiang, Yu, et autres
Publié: (2024)
par: Jiang, Yu, et autres
Publié: (2024)
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications
par: Raza, Ali, et autres
Publié: (2022)
par: Raza, Ali, et autres
Publié: (2022)
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity
par: Yi, Kai, et autres
Publié: (2024)
par: Yi, Kai, et autres
Publié: (2024)
SoK: Benchmarking Poisoning Attacks and Defenses in Federated Learning
par: Zhang, Heyi, et autres
Publié: (2025)
par: Zhang, Heyi, et autres
Publié: (2025)
SecureLearn -- An Attack-agnostic Defense for Multiclass Machine Learning Against Data Poisoning Attacks
par: Paracha, Anum, et autres
Publié: (2025)
par: Paracha, Anum, et autres
Publié: (2025)
Indiscriminate Data Poisoning Attacks on Neural Networks
par: Lu, Yiwei, et autres
Publié: (2022)
par: Lu, Yiwei, et autres
Publié: (2022)
PoisonedParrot: Subtle Data Poisoning Attacks to Elicit Copyright-Infringing Content from Large Language Models
par: Panaitescu-Liess, Michael-Andrei, et autres
Publié: (2025)
par: Panaitescu-Liess, Michael-Andrei, et autres
Publié: (2025)
FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning
par: Fereidooni, Hossein, et autres
Publié: (2023)
par: Fereidooni, Hossein, et autres
Publié: (2023)
FedRDF: A Robust and Dynamic Aggregation Function against Poisoning Attacks in Federated Learning
par: Campos, Enrique Mármol, et autres
Publié: (2024)
par: Campos, Enrique Mármol, et autres
Publié: (2024)
SAFELOC: Overcoming Data Poisoning Attacks in Heterogeneous Federated Machine Learning for Indoor Localization
par: Singampalli, Akhil, et autres
Publié: (2024)
par: Singampalli, Akhil, et autres
Publié: (2024)
Inverting Gradient Attacks Makes Powerful Data Poisoning
par: Bouaziz, Wassim, et autres
Publié: (2024)
par: Bouaziz, Wassim, et autres
Publié: (2024)
Devil's Hand: Data Poisoning Attacks to Locally Private Graph Learning Protocols
par: He, Longzhu, et autres
Publié: (2025)
par: He, Longzhu, et autres
Publié: (2025)
GFCL: A GRU-based Federated Continual Learning Framework against Data Poisoning Attacks in IoV
par: Talpur, Anum, et autres
Publié: (2022)
par: Talpur, Anum, et autres
Publié: (2022)
FedMID: A Data-Free Method for Using Intermediate Outputs as a Defense Mechanism Against Poisoning Attacks in Federated Learning
par: Han, Sungwon, et autres
Publié: (2024)
par: Han, Sungwon, et autres
Publié: (2024)
How to Defend Against Large-scale Model Poisoning Attacks in Federated Learning: A Vertical Solution
par: Wang, Jinbo, et autres
Publié: (2024)
par: Wang, Jinbo, et autres
Publié: (2024)
Online Poisoning Attack Against Reinforcement Learning under Black-box Environments
par: Li, Jianhui, et autres
Publié: (2024)
par: Li, Jianhui, et autres
Publié: (2024)
Poisoning Attacks to Local Differential Privacy Protocols for Trajectory Data
par: Hsu, I-Jung, et autres
Publié: (2025)
par: Hsu, I-Jung, et autres
Publié: (2025)
Indiscriminate Data Poisoning Attacks on Pre-trained Feature Extractors
par: Lu, Yiwei, et autres
Publié: (2024)
par: Lu, Yiwei, et autres
Publié: (2024)
Data Poisoning Attacks in Intelligent Transportation Systems: A Survey
par: Wang, Feilong, et autres
Publié: (2024)
par: Wang, Feilong, et autres
Publié: (2024)
Detecting Sybil Addresses in Blockchain Airdrops: A Subgraph-based Feature Propagation and Fusion Approach
par: Liu, Qiangqiang, et autres
Publié: (2025)
par: Liu, Qiangqiang, et autres
Publié: (2025)
Transferable Availability Poisoning Attacks
par: Liu, Yiyong, et autres
Publié: (2023)
par: Liu, Yiyong, et autres
Publié: (2023)
Poisoned-MRAG: Knowledge Poisoning Attacks to Multimodal Retrieval Augmented Generation
par: Liu, Yinuo, et autres
Publié: (2025)
par: Liu, Yinuo, et autres
Publié: (2025)
Data Poisoning Attacks to Locally Differentially Private Range Query Protocols
par: Liao, Ting-Wei, et autres
Publié: (2025)
par: Liao, Ting-Wei, et autres
Publié: (2025)
Hiding Backdoors within Event Sequence Data via Poisoning Attacks
par: Ermilova, Alina, et autres
Publié: (2023)
par: Ermilova, Alina, et autres
Publié: (2023)
RAIFLE: Reconstruction Attacks on Interaction-based Federated Learning with Adversarial Data Manipulation
par: Pham, Dzung, et autres
Publié: (2023)
par: Pham, Dzung, et autres
Publié: (2023)
Lurking in the shadows: Unveiling Stealthy Backdoor Attacks against Personalized Federated Learning
par: Lyu, Xiaoting, et autres
Publié: (2024)
par: Lyu, Xiaoting, et autres
Publié: (2024)
Poison with Style: A Practical Poisoning Attack on Code Large Language Models
par: Tran, Khang, et autres
Publié: (2026)
par: Tran, Khang, et autres
Publié: (2026)
ACE: A Model Poisoning Attack on Contribution Evaluation Methods in Federated Learning
par: Xu, Zhangchen, et autres
Publié: (2024)
par: Xu, Zhangchen, et autres
Publié: (2024)
Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks
par: Gosch, Lukas, et autres
Publié: (2024)
par: Gosch, Lukas, et autres
Publié: (2024)
Can In-Context Reinforcement Learning Recover From Reward Poisoning Attacks?
par: Sasnauskas, Paulius, et autres
Publié: (2025)
par: Sasnauskas, Paulius, et autres
Publié: (2025)
Comments on "Privacy-Enhanced Federated Learning Against Poisoning Adversaries"
par: Schneider, Thomas, et autres
Publié: (2024)
par: Schneider, Thomas, et autres
Publié: (2024)
On the Efficiency of Privacy Attacks in Federated Learning
par: Tabassum, Nawrin, et autres
Publié: (2024)
par: Tabassum, Nawrin, et autres
Publié: (2024)
Documents similaires
-
Byzantine-Robust Federated Learning: An Overview With Focus on Developing Sybil-based Attacks to Backdoor Augmented Secure Aggregation Protocols
par: Deshmukh, Atharv
Publié: (2024) -
GShield: Mitigating Poisoning Attacks in Federated Learning
par: M., Sameera K., et autres
Publié: (2025) -
Provable Watermarking for Data Poisoning Attacks
par: Zhu, Yifan, et autres
Publié: (2025) -
Local Environment Poisoning Attacks on Federated Reinforcement Learning
par: Ma, Evelyn, et autres
Publié: (2023) -
Defending Against Sophisticated Poisoning Attacks with RL-based Aggregation in Federated Learning
par: Wang, Yujing, et autres
Publié: (2024)