GFCL: A GRU-based Federated Continual Learning Framework against Data Poisoning Attacks in IoV
Fuente:
arXiv
Guardado en:
| Autores principales: | Talpur, Anum, Gurusamy, Mohan |
|---|---|
| Formato: | Preprint |
| Publicado: |
2022
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Random Forest Stratified K-Fold Cross Validation on SYN DoS Attack SD-IoV
por: Zamrai, Muhammad Arif Hakimi, et al.
Publicado: (2025)
por: Zamrai, Muhammad Arif Hakimi, et al.
Publicado: (2025)
SAFELOC: Overcoming Data Poisoning Attacks in Heterogeneous Federated Machine Learning for Indoor Localization
por: Singampalli, Akhil, et al.
Publicado: (2024)
por: Singampalli, Akhil, et al.
Publicado: (2024)
Accelerating IoV Intrusion Detection: Benchmarking GPU-Accelerated vs CPU-Based ML Libraries
por: Çolhak, Furkan, et al.
Publicado: (2025)
por: Çolhak, Furkan, et al.
Publicado: (2025)
SoK: Benchmarking Poisoning Attacks and Defenses in Federated Learning
por: Zhang, Heyi, et al.
Publicado: (2025)
por: Zhang, Heyi, et al.
Publicado: (2025)
Universal Black-Box Reward Poisoning Attack against Offline Reinforcement Learning
por: Xu, Yinglun, et al.
Publicado: (2024)
por: Xu, Yinglun, et al.
Publicado: (2024)
Zero-X: A Blockchain-Enabled Open-Set Federated Learning Framework for Zero-Day Attack Detection in IoV
por: korba, Abdelaziz Amara, et al.
Publicado: (2024)
por: korba, Abdelaziz Amara, et al.
Publicado: (2024)
ACE: A Model Poisoning Attack on Contribution Evaluation Methods in Federated Learning
por: Xu, Zhangchen, et al.
Publicado: (2024)
por: Xu, Zhangchen, et al.
Publicado: (2024)
Have You Poisoned My Data? Defending Neural Networks against Data Poisoning
por: De Gaspari, Fabio, et al.
Publicado: (2024)
por: De Gaspari, Fabio, et al.
Publicado: (2024)
EAB-FL: Exacerbating Algorithmic Bias through Model Poisoning Attacks in Federated Learning
por: Meerza, Syed Irfan Ali, et al.
Publicado: (2024)
por: Meerza, Syed Irfan Ali, et al.
Publicado: (2024)
Enhancing IoT Security Against DDoS Attacks through Federated Learning
por: Shirvani, Ghazaleh, et al.
Publicado: (2024)
por: Shirvani, Ghazaleh, et al.
Publicado: (2024)
Precision Guided Approach to Mitigate Data Poisoning Attacks in Federated Learning
por: Kumar, K Naveen, et al.
Publicado: (2024)
por: Kumar, K Naveen, et al.
Publicado: (2024)
Client-Side Patching against Backdoor Attacks in Federated Learning
por: Molina-Coronado, Borja
Publicado: (2024)
por: Molina-Coronado, Borja
Publicado: (2024)
SecureLearn -- An Attack-agnostic Defense for Multiclass Machine Learning Against Data Poisoning Attacks
por: Paracha, Anum, et al.
Publicado: (2025)
por: Paracha, Anum, et al.
Publicado: (2025)
Concealing Backdoor Model Updates in Federated Learning by Trigger-Optimized Data Poisoning
por: Zhang, Yujie, et al.
Publicado: (2024)
por: Zhang, Yujie, et al.
Publicado: (2024)
Data Poisoning Attacks on Off-Policy Policy Evaluation Methods
por: Lobo, Elita, et al.
Publicado: (2024)
por: Lobo, Elita, et al.
Publicado: (2024)
Protecting Federated Learning from Extreme Model Poisoning Attacks via Multidimensional Time Series Anomaly Detection
por: Gabrielli, Edoardo, et al.
Publicado: (2023)
por: Gabrielli, Edoardo, et al.
Publicado: (2023)
Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models
por: Xu, Yuancheng, et al.
Publicado: (2024)
por: Xu, Yuancheng, et al.
Publicado: (2024)
Defending the Edge: Representative-Attention Defense against Backdoor Attacks in Federated Learning
por: Obioma, Chibueze Peace, et al.
Publicado: (2025)
por: Obioma, Chibueze Peace, et al.
Publicado: (2025)
Data Overvaluation Attack and Truthful Data Valuation in Federated Learning
por: Zheng, Shuyuan, et al.
Publicado: (2025)
por: Zheng, Shuyuan, et al.
Publicado: (2025)
Federated Learning Resilient to Byzantine Attacks and Data Heterogeneity
por: Zuo, Shiyuan, et al.
Publicado: (2024)
por: Zuo, Shiyuan, et al.
Publicado: (2024)
UIFV: Data Reconstruction Attack in Vertical Federated Learning
por: Yang, Jirui, et al.
Publicado: (2024)
por: Yang, Jirui, et al.
Publicado: (2024)
Poisoning Attacks on Federated Learning for Autonomous Driving
por: Garg, Sonakshi, et al.
Publicado: (2024)
por: Garg, Sonakshi, et al.
Publicado: (2024)
False Data Injection Attack Detection in Edge-based Smart Metering Networks with Federated Learning
por: Uddin, Md Raihan, et al.
Publicado: (2024)
por: Uddin, Md Raihan, et al.
Publicado: (2024)
Stealthy Poisoning Attacks Bypass Defenses in Regression Settings
por: Carnerero-Cano, Javier, et al.
Publicado: (2026)
por: Carnerero-Cano, Javier, et al.
Publicado: (2026)
Be Kind, Rewrite: Benign Projections via Rewriting Defend Against LLM Data Poisoning Attacks
por: Halloran, John T., et al.
Publicado: (2026)
por: Halloran, John T., et al.
Publicado: (2026)
Defending Against Poisoning Attacks in Federated Learning with Blockchain
por: Dong, Nanqing, et al.
Publicado: (2023)
por: Dong, Nanqing, et al.
Publicado: (2023)
Enhancing IoT Cyber Attack Detection in the Presence of Highly Imbalanced Data
por: Haque, Md. Ehsanul, et al.
Publicado: (2025)
por: Haque, Md. Ehsanul, et al.
Publicado: (2025)
FedReview: A Review Mechanism for Rejecting Poisoned Updates in Federated Learning
por: Zheng, Tianhang, et al.
Publicado: (2024)
por: Zheng, Tianhang, et al.
Publicado: (2024)
FedCC: Robust Federated Learning against Model Poisoning Attacks
por: Jeong, Hyejun, et al.
Publicado: (2022)
por: Jeong, Hyejun, et al.
Publicado: (2022)
Similarity-based Label Inference Attack against Training and Inference of Split Learning
por: Liu, Junlin, et al.
Publicado: (2022)
por: Liu, Junlin, et al.
Publicado: (2022)
Sybil-based Virtual Data Poisoning Attacks in Federated Learning
por: Zhu, Changxun, et al.
Publicado: (2025)
por: Zhu, Changxun, et al.
Publicado: (2025)
Lightweight MobileNetV1+GRU for ECG Biometric Authentication: Federated and Adversarial Evaluation
por: Rai, Dilli Hang, et al.
Publicado: (2025)
por: Rai, Dilli Hang, et al.
Publicado: (2025)
BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning
por: Liu, Yi, et al.
Publicado: (2024)
por: Liu, Yi, et al.
Publicado: (2024)
Machine Unlearning Fails to Remove Data Poisoning Attacks
por: Pawelczyk, Martin, et al.
Publicado: (2024)
por: Pawelczyk, Martin, et al.
Publicado: (2024)
Semantic Chameleon: Corpus-Dependent Poisoning Attacks and Defenses in RAG Systems
por: Thornton, Scott
Publicado: (2026)
por: Thornton, Scott
Publicado: (2026)
Scaling Trends for Data Poisoning in LLMs
por: Bowen, Dillon, et al.
Publicado: (2024)
por: Bowen, Dillon, et al.
Publicado: (2024)
Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated Learning
por: Diana, Francesco, et al.
Publicado: (2025)
por: Diana, Francesco, et al.
Publicado: (2025)
Federated Learning Under Attack: Exposing Vulnerabilities through Data Poisoning Attacks in Computer Networks
por: Nowroozi, Ehsan, et al.
Publicado: (2024)
por: Nowroozi, Ehsan, et al.
Publicado: (2024)
Partner in Crime: Boosting Targeted Poisoning Attacks against Federated Learning
por: Sun, Shihua, et al.
Publicado: (2024)
por: Sun, Shihua, et al.
Publicado: (2024)
Best-of-Venom: Attacking RLHF by Injecting Poisoned Preference Data
por: Baumgärtner, Tim, et al.
Publicado: (2024)
por: Baumgärtner, Tim, et al.
Publicado: (2024)
Ejemplares similares
-
Random Forest Stratified K-Fold Cross Validation on SYN DoS Attack SD-IoV
por: Zamrai, Muhammad Arif Hakimi, et al.
Publicado: (2025) -
SAFELOC: Overcoming Data Poisoning Attacks in Heterogeneous Federated Machine Learning for Indoor Localization
por: Singampalli, Akhil, et al.
Publicado: (2024) -
Accelerating IoV Intrusion Detection: Benchmarking GPU-Accelerated vs CPU-Based ML Libraries
por: Çolhak, Furkan, et al.
Publicado: (2025) -
SoK: Benchmarking Poisoning Attacks and Defenses in Federated Learning
por: Zhang, Heyi, et al.
Publicado: (2025) -
Universal Black-Box Reward Poisoning Attack against Offline Reinforcement Learning
por: Xu, Yinglun, et al.
Publicado: (2024)