GShield: Mitigating Poisoning Attacks in Federated Learning
Fuente:
arXiv
Saved in:
| Main Authors: | M., Sameera K., Nicolazzo, Serena, Nocera, Antonino, P., Vinod, A, Rafidha Rehiman K. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Privacy-Preserving in Blockchain-based Federated Learning Systems
by: M., Sameera K., et al.
Published: (2024)
by: M., Sameera K., et al.
Published: (2024)
KDk: A Defense Mechanism Against Label Inference Attacks in Vertical Federated Learning
by: Arazzi, Marco, et al.
Published: (2024)
by: Arazzi, Marco, et al.
Published: (2024)
Towards Certified Malware Detection: Provable Guarantees Against Evasion Attacks
by: Giri, Nandakrishna, et al.
Published: (2026)
by: Giri, Nandakrishna, et al.
Published: (2026)
WeiDetect: Weibull Distribution-Based Defense against Poisoning Attacks in Federated Learning for Network Intrusion Detection Systems
by: M., Sameera K., et al.
Published: (2025)
by: M., Sameera K., et al.
Published: (2025)
Enhancing Android Malware Detection with Retrieval-Augmented Generation
by: S., Saraga, et al.
Published: (2025)
by: S., Saraga, et al.
Published: (2025)
DroidTTP: Mapping Android Applications with TTP for Cyber Threat Intelligence
by: Arikkat, Dincy R, et al.
Published: (2025)
by: Arikkat, Dincy R, et al.
Published: (2025)
SeCTIS: A Framework to Secure CTI Sharing
by: Arikkat, Dincy R., et al.
Published: (2024)
by: Arikkat, Dincy R., et al.
Published: (2024)
A Novel IoT Trust Model Leveraging Fully Distributed Behavioral Fingerprinting and Secure Delegation
by: Arazzi, Marco, et al.
Published: (2023)
by: Arazzi, Marco, et al.
Published: (2023)
How Secure is Forgetting? Linking Machine Unlearning to Machine Learning Attacks
by: P., Muhammed Shafi K., et al.
Published: (2025)
by: P., Muhammed Shafi K., et al.
Published: (2025)
Security through the Eyes of AI: How Visualization is Shaping Malware Detection
by: Brosolo, Matteo, et al.
Published: (2025)
by: Brosolo, Matteo, et al.
Published: (2025)
CTI Dataset Construction from Telegram
by: Arikkat, Dincy R., et al.
Published: (2025)
by: Arikkat, Dincy R., et al.
Published: (2025)
A Deep Reinforcement Learning Approach for Security-Aware Service Acquisition in IoT
by: Arazzi, Marco, et al.
Published: (2024)
by: Arazzi, Marco, et al.
Published: (2024)
Let's Focus: Focused Backdoor Attack against Federated Transfer Learning
by: Arazzi, Marco, et al.
Published: (2024)
by: Arazzi, Marco, et al.
Published: (2024)
Secure Federated Data Distillation
by: Arazzi, Marco, et al.
Published: (2025)
by: Arazzi, Marco, et al.
Published: (2025)
Service Level Agreements and Security SLA: A Comprehensive Survey
by: Nicolazzo, Serena, et al.
Published: (2024)
by: Nicolazzo, Serena, et al.
Published: (2024)
FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning
by: Fereidooni, Hossein, et al.
Published: (2023)
by: Fereidooni, Hossein, et al.
Published: (2023)
Label Inference Attacks against Node-level Vertical Federated GNNs
by: Arazzi, Marco, et al.
Published: (2023)
by: Arazzi, Marco, et al.
Published: (2023)
Deep Learning Fusion For Effective Malware Detection: Leveraging Visual Features
by: Johny, Jahez Abraham, et al.
Published: (2024)
by: Johny, Jahez Abraham, et al.
Published: (2024)
When Forgetting Triggers Backdoors: A Clean Unlearning Attack
by: Arazzi, Marco, et al.
Published: (2025)
by: Arazzi, Marco, et al.
Published: (2025)
Privacy Preserving and Robust Aggregation for Cross-Silo Federated Learning in Non-IID Settings
by: Arazzi, Marco, et al.
Published: (2025)
by: Arazzi, Marco, et al.
Published: (2025)
Local Environment Poisoning Attacks on Federated Reinforcement Learning
by: Ma, Evelyn, et al.
Published: (2023)
by: Ma, Evelyn, et al.
Published: (2023)
XBreaking: Understanding how LLMs security alignment can be broken
by: Arazzi, Marco, et al.
Published: (2025)
by: Arazzi, Marco, et al.
Published: (2025)
Sybil-based Virtual Data Poisoning Attacks in Federated Learning
by: Zhu, Changxun, et al.
Published: (2025)
by: Zhu, Changxun, et al.
Published: (2025)
FedRecAttack: Model Poisoning Attack to Federated Recommendation
by: Rong, Dazhong, et al.
Published: (2022)
by: Rong, Dazhong, et al.
Published: (2022)
Partner in Crime: Boosting Targeted Poisoning Attacks against Federated Learning
by: Sun, Shihua, et al.
Published: (2024)
by: Sun, Shihua, et al.
Published: (2024)
Towards Efficient and Certified Recovery from Poisoning Attacks in Federated Learning
by: Jiang, Yu, et al.
Published: (2024)
by: Jiang, Yu, et al.
Published: (2024)
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications
by: Raza, Ali, et al.
Published: (2022)
by: Raza, Ali, et al.
Published: (2022)
Defending Against Sophisticated Poisoning Attacks with RL-based Aggregation in Federated Learning
by: Wang, Yujing, et al.
Published: (2024)
by: Wang, Yujing, et al.
Published: (2024)
Protecting Deep Neural Network Intellectual Property with Chaos-Based White-Box Watermarking
by: B, Sangeeth, et al.
Published: (2025)
by: B, Sangeeth, et al.
Published: (2025)
FedRDF: A Robust and Dynamic Aggregation Function against Poisoning Attacks in Federated Learning
by: Campos, Enrique Mármol, et al.
Published: (2024)
by: Campos, Enrique Mármol, et al.
Published: (2024)
A Data-Driven Defense against Edge-case Model Poisoning Attacks on Federated Learning
by: Purohit, Kiran, et al.
Published: (2023)
by: Purohit, Kiran, et al.
Published: (2023)
Discerning Reliable Cyber Threat Indicators for Timely Cyber Threat Intelligence
by: Arikkat, Dincy R, et al.
Published: (2023)
by: Arikkat, Dincy R, et al.
Published: (2023)
SoK: Benchmarking Poisoning Attacks and Defenses in Federated Learning
by: Zhang, Heyi, et al.
Published: (2025)
by: Zhang, Heyi, et al.
Published: (2025)
How to Defend Against Large-scale Model Poisoning Attacks in Federated Learning: A Vertical Solution
by: Wang, Jinbo, et al.
Published: (2024)
by: Wang, Jinbo, et al.
Published: (2024)
Transferable Availability Poisoning Attacks
by: Liu, Yiyong, et al.
Published: (2023)
by: Liu, Yiyong, et al.
Published: (2023)
SecureLearn -- An Attack-agnostic Defense for Multiclass Machine Learning Against Data Poisoning Attacks
by: Paracha, Anum, et al.
Published: (2025)
by: Paracha, Anum, et al.
Published: (2025)
Poisoned-MRAG: Knowledge Poisoning Attacks to Multimodal Retrieval Augmented Generation
by: Liu, Yinuo, et al.
Published: (2025)
by: Liu, Yinuo, et al.
Published: (2025)
Enhancing the Antidote: Improved Pointwise Certifications against Poisoning Attacks
by: Liu, Shijie, et al.
Published: (2023)
by: Liu, Shijie, et al.
Published: (2023)
Provable Watermarking for Data Poisoning Attacks
by: Zhu, Yifan, et al.
Published: (2025)
by: Zhu, Yifan, et al.
Published: (2025)
ACE: A Model Poisoning Attack on Contribution Evaluation Methods in Federated Learning
by: Xu, Zhangchen, et al.
Published: (2024)
by: Xu, Zhangchen, et al.
Published: (2024)
Similar Items
-
Privacy-Preserving in Blockchain-based Federated Learning Systems
by: M., Sameera K., et al.
Published: (2024) -
KDk: A Defense Mechanism Against Label Inference Attacks in Vertical Federated Learning
by: Arazzi, Marco, et al.
Published: (2024) -
Towards Certified Malware Detection: Provable Guarantees Against Evasion Attacks
by: Giri, Nandakrishna, et al.
Published: (2026) -
WeiDetect: Weibull Distribution-Based Defense against Poisoning Attacks in Federated Learning for Network Intrusion Detection Systems
by: M., Sameera K., et al.
Published: (2025) -
Enhancing Android Malware Detection with Retrieval-Augmented Generation
by: S., Saraga, et al.
Published: (2025)