Privacy Risks Analysis and Mitigation in Federated Learning for Medical Images
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | Das, Badhan Chandra, Amini, M. Hadi, Wu, Yanzhao |
|---|---|
| Format: | Preprint |
| Publié: |
2023
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
In-depth Analysis of Privacy Threats in Federated Learning for Medical Data
par: Das, Badhan Chandra, et autres
Publié: (2024)
par: Das, Badhan Chandra, et autres
Publié: (2024)
Security and Privacy Challenges of Large Language Models: A Survey
par: Das, Badhan Chandra, et autres
Publié: (2024)
par: Das, Badhan Chandra, et autres
Publié: (2024)
Accurate and Efficient Two-Stage Gun Detection in Video
par: Das, Badhan Chandra, et autres
Publié: (2025)
par: Das, Badhan Chandra, et autres
Publié: (2025)
System Prompt Extraction Attacks and Defenses in Large Language Models
par: Das, Badhan Chandra, et autres
Publié: (2025)
par: Das, Badhan Chandra, et autres
Publié: (2025)
Heterogeneous Federated Reinforcement Learning Using Wasserstein Barycenters
par: Pereira, Luiz, et autres
Publié: (2025)
par: Pereira, Luiz, et autres
Publié: (2025)
On the Efficiency of Privacy Attacks in Federated Learning
par: Tabassum, Nawrin, et autres
Publié: (2024)
par: Tabassum, Nawrin, et autres
Publié: (2024)
Multi-turn Jailbreaking Attack in Multi-Modal Large Language Models
par: Das, Badhan Chandra, et autres
Publié: (2026)
par: Das, Badhan Chandra, et autres
Publié: (2026)
Hyper-parameter Optimization for Federated Learning with Step-wise Adaptive Mechanism
par: Saadati, Yasaman, et autres
Publié: (2024)
par: Saadati, Yasaman, et autres
Publié: (2024)
Optimal Transport-based Domain Alignment as a Preprocessing Step for Federated Learning
par: Pereira, Luiz Manella, et autres
Publié: (2025)
par: Pereira, Luiz Manella, et autres
Publié: (2025)
Jailbreaking Large Vision Language Models in Intelligent Transportation Systems
par: Das, Badhan Chandra, et autres
Publié: (2025)
par: Das, Badhan Chandra, et autres
Publié: (2025)
SegResMamba: An Efficient Architecture for 3D Medical Image Segmentation
par: Das, Badhan Kumar, et autres
Publié: (2025)
par: Das, Badhan Kumar, et autres
Publié: (2025)
pMixFed: Efficient Personalized Federated Learning through Adaptive Layer-Wise Mixup
par: Saadati, Yasaman, et autres
Publié: (2025)
par: Saadati, Yasaman, et autres
Publié: (2025)
Boosting Deep Ensembles with Learning Rate Tuning
par: Jin, Hongpeng, et autres
Publié: (2024)
par: Jin, Hongpeng, et autres
Publié: (2024)
Mechanical Strength Prediction of Steel-Polypropylene Fiber-based High-Performance Concrete Using Hybrid Machine Learning Algorithms
par: Chakma, Jagaran, et autres
Publié: (2025)
par: Chakma, Jagaran, et autres
Publié: (2025)
Mitigating Data Absence in Federated Learning Using Privacy-Controllable Data Digests
par: Hsu, Chih-Fan, et autres
Publié: (2022)
par: Hsu, Chih-Fan, et autres
Publié: (2022)
Metric Privacy in Federated Learning for Medical Imaging: Improving Convergence and Preventing Client Inference Attacks
par: Díaz, Judith Sáinz-Pardo, et autres
Publié: (2025)
par: Díaz, Judith Sáinz-Pardo, et autres
Publié: (2025)
Privacy Preserving Federated Learning in Medical Imaging with Uncertainty Estimation
par: Koutsoubis, Nikolas, et autres
Publié: (2024)
par: Koutsoubis, Nikolas, et autres
Publié: (2024)
FinP: Fairness-in-Privacy in Federated Learning by Addressing Disparities in Privacy Risk
par: Zhao, Tianyu, et autres
Publié: (2025)
par: Zhao, Tianyu, et autres
Publié: (2025)
Blockchain-Empowered Cyber-Secure Federated Learning for Trustworthy Edge Computing
par: Moore, Ervin, et autres
Publié: (2024)
par: Moore, Ervin, et autres
Publié: (2024)
Privacy-Preserving Federated Learning via Differential Privacy and Homomorphic Encryption for Cardiovascular Disease Risk Modeling
par: Sharma, Gaurang, et autres
Publié: (2026)
par: Sharma, Gaurang, et autres
Publié: (2026)
Adaptive Coded Federated Learning: Privacy Preservation and Straggler Mitigation
par: Li, Chengxi, et autres
Publié: (2024)
par: Li, Chengxi, et autres
Publié: (2024)
CorBin-FL: A Differentially Private Federated Learning Mechanism using Common Randomness
par: Salehi, Hojat Allah, et autres
Publié: (2024)
par: Salehi, Hojat Allah, et autres
Publié: (2024)
Federated Learning for Privacy-Preserving Medical AI
par: Hoang, Tin
Publié: (2026)
par: Hoang, Tin
Publié: (2026)
Towards Privacy-Preserving Medical Imaging: Federated Learning with Differential Privacy and Secure Aggregation Using a Modified ResNet Architecture
par: Fares, Mohamad Haj, et autres
Publié: (2024)
par: Fares, Mohamad Haj, et autres
Publié: (2024)
Federated Continual Learning for Privacy-Preserving Hospital Imaging Classification
par: Sinhal, Anay, et autres
Publié: (2026)
par: Sinhal, Anay, et autres
Publié: (2026)
From Risk to Resilience: Towards Assessing and Mitigating the Risk of Data Reconstruction Attacks in Federated Learning
par: Xu, Xiangrui, et autres
Publié: (2025)
par: Xu, Xiangrui, et autres
Publié: (2025)
Mitigating Privacy Risk via Forget Set-Free Unlearning
par: Newatia, Aviraj, et autres
Publié: (2026)
par: Newatia, Aviraj, et autres
Publié: (2026)
When Differential Privacy Meets Wireless Federated Learning: An Improved Analysis for Privacy and Convergence
par: Yaoling, Chen, et autres
Publié: (2026)
par: Yaoling, Chen, et autres
Publié: (2026)
On the Fairness of Privacy Protection: Measuring and Mitigating the Disparity of Group Privacy Risks for Differentially Private Machine Learning
par: Yang, Zhi, et autres
Publié: (2025)
par: Yang, Zhi, et autres
Publié: (2025)
Lossless Privacy-Preserving Aggregation for Decentralized Federated Learning
par: Miao, Xiaoye, et autres
Publié: (2025)
par: Miao, Xiaoye, et autres
Publié: (2025)
Privacy-Preserving Federated Learning for Fair and Efficient Urban Traffic Optimization
par: Shit, Rathin Chandra, et autres
Publié: (2025)
par: Shit, Rathin Chandra, et autres
Publié: (2025)
Mitigating Privacy-Utility Trade-off in Decentralized Federated Learning via $f$-Differential Privacy
par: Li, Xiang, et autres
Publié: (2025)
par: Li, Xiang, et autres
Publié: (2025)
Convergent Differential Privacy Analysis for General Federated Learning
par: Sun, Yan, et autres
Publié: (2024)
par: Sun, Yan, et autres
Publié: (2024)
FedVCK: Non-IID Robust and Communication-Efficient Federated Learning via Valuable Condensed Knowledge for Medical Image Analysis
par: Yan, Guochen, et autres
Publié: (2024)
par: Yan, Guochen, et autres
Publié: (2024)
DriftGuard: Mitigating Asynchronous Data Drift in Federated Learning
par: Han, Yizhou, et autres
Publié: (2026)
par: Han, Yizhou, et autres
Publié: (2026)
Privacy-Preserving Federated Learning via Dataset Distillation
par: Xu, ShiMao, et autres
Publié: (2024)
par: Xu, ShiMao, et autres
Publié: (2024)
Accuracy-Privacy Trade-off in the Mitigation of Membership Inference Attack in Federated Learning
par: Ahamed, Sayyed Farid, et autres
Publié: (2024)
par: Ahamed, Sayyed Farid, et autres
Publié: (2024)
Communication-Efficient and Privacy-Adaptable Mechanism for Federated Learning
par: Ling, Chih Wei, et autres
Publié: (2025)
par: Ling, Chih Wei, et autres
Publié: (2025)
Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss
par: Liu, Zhenlong, et autres
Publié: (2024)
par: Liu, Zhenlong, et autres
Publié: (2024)
FL-PBM: Pre-Training Backdoor Mitigation for Federated Learning
par: Wehbi, Osama, et autres
Publié: (2026)
par: Wehbi, Osama, et autres
Publié: (2026)
Documents similaires
-
In-depth Analysis of Privacy Threats in Federated Learning for Medical Data
par: Das, Badhan Chandra, et autres
Publié: (2024) -
Security and Privacy Challenges of Large Language Models: A Survey
par: Das, Badhan Chandra, et autres
Publié: (2024) -
Accurate and Efficient Two-Stage Gun Detection in Video
par: Das, Badhan Chandra, et autres
Publié: (2025) -
System Prompt Extraction Attacks and Defenses in Large Language Models
par: Das, Badhan Chandra, et autres
Publié: (2025) -
Heterogeneous Federated Reinforcement Learning Using Wasserstein Barycenters
par: Pereira, Luiz, et autres
Publié: (2025)