:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhang, Xueqing, Zhang, Junkai, Chow, Ka-Ho, Chen, Juntao, Mao, Ying, Rahouti, Mohamed, Li, Xiang, Liu, Yuchen, Wei, Wenqi
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security
Online Access:	https://arxiv.org/abs/2405.16707
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Harmless Backdoor-based Client-side Watermarking in Federated Learning
by: Luo, Kaijing, et al.
Published: (2024)

Imperio: Language-Guided Backdoor Attacks for Arbitrary Model Control
by: Chow, Ka-Ho, et al.
Published: (2024)

Building Gradient Bridges: Label Leakage from Restricted Gradient Sharing in Federated Learning
by: Zhang, Rui, et al.
Published: (2024)

Confundo: Learning to Generate Robust Poison for Practical RAG Systems
by: Hu, Haoyang, et al.
Published: (2026)

On the Adversarial Robustness of Graph Neural Networks with Graph Reduction
by: Wu, Kerui, et al.
Published: (2024)

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

Next-Generation Phishing: How LLM Agents Empower Cyber Attackers
by: Afane, Khalifa, et al.
Published: (2024)

Geminio: Language-Guided Gradient Inversion Attacks in Federated Learning
by: Shan, Junjie, et al.
Published: (2024)

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

Learning in Multiple Spaces: Few-Shot Network Attack Detection with Metric-Fused Prototypical Networks
by: Martinez-Lopez, Fernando, et al.
Published: (2024)

SCOUT: A Defense Against Data Poisoning Attacks in Fine-Tuned Language Models
by: Afane, Mohamed, et al.
Published: (2025)

ProtegoFed: Backdoor-Free Federated Instruction Tuning with Interspersed Poisoned Data
by: Zhao, Haodong, et al.
Published: (2026)

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

Integrating Robotic Navigation with Blockchain: A Novel PoS-Based Approach for Heterogeneous Robotic Teams
by: Paykari, Nasim, et al.
Published: (2025)

A Secure Blockchain-Assisted Framework for Real-Time Maritime Environmental Compliance Monitoring
by: Quigley, William C., et al.
Published: (2025)

Poisoning Attacks and Defenses to Federated Unlearning
by: Wang, Wenbin, et al.
Published: (2025)

Poisoning Attacks on Federated Learning-based Wireless Traffic Prediction
by: Zhang, Zifan, et al.
Published: (2024)

Data Poisoning for In-context Learning
by: He, Pengfei, et al.
Published: (2024)

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

Privacy-Preserving Federated Learning Scheme with Mitigating Model Poisoning Attacks: Vulnerabilities and Countermeasures
by: Wu, Jiahui, et al.
Published: (2025)

VisPoison: An Effective Backdoor Attack Framework for Tabular Data Visualization Models
by: Li, Shuaimin, et al.
Published: (2024)

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

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

A Survey of Privacy Threats and Defense in Vertical Federated Learning: From Model Life Cycle Perspective
by: Yu, Lei, et al.
Published: (2024)

Leverage Variational Graph Representation For Model Poisoning on Federated Learning
by: Li, Kai, et al.
Published: (2024)

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

Nonlinear Transformations Against Unlearnable Datasets
by: Hapuarachchi, Thushari, et al.
Published: (2024)

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

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

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

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

Safely Learning with Private Data: A Federated Learning Framework for Large Language Model
by: Zheng, JiaYing, et al.
Published: (2024)

Towards Efficient and Certified Recovery from Poisoning Attacks in Federated Learning
by: Jiang, Yu, et al.
Published: (2024)

Defending Against Sophisticated Poisoning Attacks with RL-based Aggregation in Federated Learning
by: Wang, Yujing, et al.
Published: (2024)

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

EnCAgg: Enhanced Clustering Aggregation for Robust Federated Learning against Dynamic Model Poisoning
by: Zhang, Tianyun, et al.
Published: (2026)

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

PACE: Poisoning Attacks on Learned Cardinality Estimation
by: Zhang, Jintao, et al.
Published: (2024)

Local Environment Poisoning Attacks on Federated Reinforcement Learning
by: Ma, Evelyn, et al.
Published: (2023)

Poison to Detect: Detection of Targeted Overfitting in Federated Learning
by: Mestari, Soumia Zohra El, et al.
Published: (2025)