Cover Image

Privacy-Preserving Federated Learning Scheme with Mitigating Model Poisoning Attacks: Vulnerabilities and Countermeasures

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wu, Jiahui, Luo, Fucai, Sun, Tiecheng, Wang, Haiyan, Zhang, Weizhe
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Secure Multi-Key Homomorphic Encryption with Application to Privacy-Preserving Federated Learning
by: Wu, Jiahui, et al.
Published: (2025)

Logit Poisoning Attack in Distillation-based Federated Learning and its Countermeasures
by: Yu, Yonghao, et al.
Published: (2024)

Mitigating Data Poisoning Attacks to Local Differential Privacy
by: Li, Xiaolin, et al.
Published: (2025)

Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning
by: Xu, Runhua, et al.
Published: (2025)

GShield: Mitigating Poisoning Attacks in Federated Learning
by: M., Sameera K., et al.
Published: (2025)

A Model Consistency-Based Countermeasure to GAN-Based Data Poisoning Attack in Federated Learning
by: Sun, Wei, et al.
Published: (2024)

Survey of Privacy Threats and Countermeasures in Federated Learning
by: Hayashitani, Masahiro, et al.
Published: (2024)

A Survey of Privacy-Preserving Model Explanations: Privacy Risks, Attacks, and Countermeasures
by: Nguyen, Thanh Tam, et al.
Published: (2024)

Denial-of-Service Vulnerability of Hash-based Transaction Sharding: Attack and Countermeasure
by: Nguyen, Truc, et al.
Published: (2020)

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

SRFed: Mitigating Poisoning Attacks in Privacy-Preserving Federated Learning with Heterogeneous Data
by: Lu, Yiwen
Published: (2026)

Manipulating Recommender Systems: A Survey of Poisoning Attacks and Countermeasures
by: Nguyen, Thanh Toan, et al.
Published: (2024)

Model Poisoning Attacks to Federated Learning via Multi-Round Consistency
by: Xie, Yueqi, et al.
Published: (2024)

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

Adversarial Attack Based Countermeasures against Deep Learning Side-Channel Attacks
by: Gu, Ruizhe, et al.
Published: (2020)

On the Efficiency of Privacy Attacks in Federated Learning
by: Tabassum, Nawrin, et al.
Published: (2024)

Modern DDoS Threats and Countermeasures: Insights into Emerging Attacks and Detection Strategies
by: Wang, Jincheng, et al.
Published: (2025)

Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks
by: Xie, Chulin, et al.
Published: (2022)

Partner in Crime: Boosting Targeted Poisoning Attacks against Federated Learning
by: Sun, Shihua, et al.
Published: (2024)

Poisoning Attacks to Local Differential Privacy for Ranking Estimation
by: Zhan, Pei, et al.
Published: (2025)

Privacy Threats and Countermeasures in Federated Learning for Internet of Things: A Systematic Review
by: ElZemity, Adel, et al.
Published: (2024)

Learning-based Privacy-Preserving Graph Publishing Against Sensitive Link Inference Attacks
by: Wu, Yucheng, et al.
Published: (2025)

PPFPL: Cross-silo Privacy-preserving Federated Prototype Learning Against Data Poisoning Attacks
by: Zhang, Hongliang, et al.
Published: (2025)

A Learning-Based Attack Framework to Break SOTA Poisoning Defenses in Federated Learning
by: Yang, Yuxin, et al.
Published: (2024)

Deciphering the Interplay between Attack and Protection Complexity in Privacy-Preserving Federated Learning
by: Zhang, Xiaojin, et al.
Published: (2025)

Sybil-based Virtual Data Poisoning Attacks in Federated Learning
by: Zhu, Changxun, et al.
Published: (2025)

LDPRecover: Recovering Frequencies from Poisoning Attacks against Local Differential Privacy
by: Sun, Xinyue, et al.
Published: (2024)

FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning
by: Fereidooni, Hossein, et al.
Published: (2023)

Poisoning Decentralized Collaborative Recommender System and Its Countermeasures
by: Zheng, Ruiqi, et al.
Published: (2024)

Differential Privacy in Federated Learning: Mitigating Inference Attacks with Randomized Response
by: Ozturk, Ozer, et al.
Published: (2025)

Poisoning Prevention in Federated Learning and Differential Privacy via Stateful Proofs of Execution
by: Rattanavipanon, Norrathep, et al.
Published: (2024)

On Evaluating the Poisoning Robustness of Federated Learning under Local Differential Privacy
by: Wang, Zijian, et al.
Published: (2025)

FedRecAttack: Model Poisoning Attack to Federated Recommendation
by: Rong, Dazhong, et al.
Published: (2022)

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

Backdoor Attacks and Countermeasures in Natural Language Processing Models: A Comprehensive Security Review
by: Cheng, Pengzhou, et al.
Published: (2023)

Defending against Data Poisoning Attacks in Federated Learning via User Elimination
by: Galanis, Nick
Published: (2024)

Efficient Byzantine-Robust and Provably Privacy-Preserving Federated Learning
by: Nie, Chenfei, et al.
Published: (2024)

Security of Internet of Agents: Attacks and Countermeasures
by: Wang, Yuntao, et al.
Published: (2025)

FedCC: Robust Federated Learning against Model Poisoning Attacks
by: Jeong, Hyejun, et al.
Published: (2022)

LLM Security: Vulnerabilities, Attacks, Defenses, and Countermeasures
by: Aguilera-Martínez, Francisco, et al.
Published: (2025)