Privacy-preserving quantum federated learning via gradient hiding
Fuente:
arXiv
Saved in:
| Main Authors: | Li, Changhao, Kumar, Niraj, Song, Zhixin, Chakrabarti, Shouvanik, Pistoia, Marco |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Improving LoRA in Privacy-preserving Federated Learning
by: Sun, Youbang, et al.
Published: (2024)
by: Sun, Youbang, et al.
Published: (2024)
FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation
by: Xia, Tong, et al.
Published: (2023)
by: Xia, Tong, et al.
Published: (2023)
Experimentally validated quantum-secure federated learning over a multi-user quantum network
by: Liu, Zhi-Ping, et al.
Published: (2025)
by: Liu, Zhi-Ping, et al.
Published: (2025)
PPFPL: Cross-silo Privacy-preserving Federated Prototype Learning Against Data Poisoning Attacks
by: Zhang, Hongliang, et al.
Published: (2025)
by: Zhang, Hongliang, et al.
Published: (2025)
A chaotic maps-based privacy-preserving distributed deep learning for incomplete and Non-IID datasets
by: Arévalo, Irina, et al.
Published: (2024)
by: Arévalo, Irina, et al.
Published: (2024)
Protecting Confidentiality, Privacy and Integrity in Collaborative Learning
by: Chen, Dong, et al.
Published: (2024)
by: Chen, Dong, et al.
Published: (2024)
The Effect of Quantization in Federated Learning: A Rényi Differential Privacy Perspective
by: Kang, Tianqu, et al.
Published: (2024)
by: Kang, Tianqu, et al.
Published: (2024)
TimberStrike: Dataset Reconstruction Attack Revealing Privacy Leakage in Federated Tree-Based Systems
by: Di Gennaro, Marco, et al.
Published: (2025)
by: Di Gennaro, Marco, et al.
Published: (2025)
Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation
by: Yan, Bo, et al.
Published: (2023)
by: Yan, Bo, et al.
Published: (2023)
Secure, Verifiable, and Scalable Multi-Client Data Sharing via Consensus-Based Privacy-Preserving Data Distribution
by: Panth, Prajwal, et al.
Published: (2026)
by: Panth, Prajwal, et al.
Published: (2026)
Balancing Privacy, Robustness, and Efficiency in Machine Learning
by: Allouah, Youssef, et al.
Published: (2023)
by: Allouah, Youssef, et al.
Published: (2023)
Privacy-First Crowdsourcing: Blockchain and Local Differential Privacy in Crowdsourced Drone Services
by: Akram, Junaid, et al.
Published: (2024)
by: Akram, Junaid, et al.
Published: (2024)
Communication-Efficient and Privacy-Preserving Decentralized Meta-Learning
by: Yang, Hansi, et al.
Published: (2024)
by: Yang, Hansi, et al.
Published: (2024)
No Vandalism: Privacy-Preserving and Byzantine-Robust Federated Learning
by: Xing, Zhibo, et al.
Published: (2024)
by: Xing, Zhibo, et al.
Published: (2024)
FedRBE -- a decentralized privacy-preserving federated batch effect correction tool for omics data based on limma
by: Burankova, Yuliya, et al.
Published: (2024)
by: Burankova, Yuliya, et al.
Published: (2024)
On Fair Ordering and Differential Privacy
by: Cohen, Shir, et al.
Published: (2025)
by: Cohen, Shir, et al.
Published: (2025)
On the Tradeoff between Privacy Preservation and Byzantine-Robustness in Decentralized Learning
by: Ye, Haoxiang, et al.
Published: (2023)
by: Ye, Haoxiang, et al.
Published: (2023)
Practical Framework for Privacy-Preserving and Byzantine-robust Federated Learning
by: Zhang, Baolei, et al.
Published: (2025)
by: Zhang, Baolei, et al.
Published: (2025)
Share Secrets for Privacy: Confidential Forecasting with Vertical Federated Learning
by: Shankar, Aditya, et al.
Published: (2024)
by: Shankar, Aditya, et al.
Published: (2024)
Decentralized Collaborative Learning Framework with External Privacy Leakage Analysis
by: Idé, Tsuyoshi, et al.
Published: (2024)
by: Idé, Tsuyoshi, et al.
Published: (2024)
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging
by: Cyffers, Edwige, et al.
Published: (2022)
by: Cyffers, Edwige, et al.
Published: (2022)
Differentially Private Federated Learning With Time-Adaptive Privacy Spending
by: Kiani, Shahrzad, et al.
Published: (2025)
by: Kiani, Shahrzad, et al.
Published: (2025)
Adaptive Differential Privacy in Federated Learning: A Priority-Based Approach
by: Talaei, Mahtab, et al.
Published: (2024)
by: Talaei, Mahtab, et al.
Published: (2024)
Enhancing Federated Learning with Adaptive Differential Privacy and Priority-Based Aggregation
by: Talaei, Mahtab, et al.
Published: (2024)
by: Talaei, Mahtab, et al.
Published: (2024)
Brave: Byzantine-Resilient and Privacy-Preserving Peer-to-Peer Federated Learning
by: Xu, Zhangchen, et al.
Published: (2024)
by: Xu, Zhangchen, et al.
Published: (2024)
Detect \& Score: Privacy-Preserving Misbehaviour Detection and Contribution Evaluation in Federated Learning
by: Xhemrishi, Marvin, et al.
Published: (2025)
by: Xhemrishi, Marvin, et al.
Published: (2025)
Enhancing Privacy in Decentralized Min-Max Optimization: A Differentially Private Approach
by: Quan, Yueyang, et al.
Published: (2025)
by: Quan, Yueyang, et al.
Published: (2025)
A Lightweight Federated Learning Approach for Privacy-Preserving Botnet Detection in IoT
by: Mahmoud, Taha M., et al.
Published: (2025)
by: Mahmoud, Taha M., et al.
Published: (2025)
Privacy Preserving Machine Learning Model Personalization through Federated Personalized Learning
by: Hosain, Md. Tanzib, et al.
Published: (2025)
by: Hosain, Md. Tanzib, et al.
Published: (2025)
Linkage on Security, Privacy and Fairness in Federated Learning: New Balances and New Perspectives
by: Wang, Linlin, et al.
Published: (2024)
by: Wang, Linlin, et al.
Published: (2024)
DPBalance: Efficient and Fair Privacy Budget Scheduling for Federated Learning as a Service
by: Liu, Yu, et al.
Published: (2024)
by: Liu, Yu, et al.
Published: (2024)
IntraShuffler: A Privacy Preserving Framework for Heterogeneous DP Federated Learning
by: Riya, Farhin Farhad, et al.
Published: (2026)
by: Riya, Farhin Farhad, et al.
Published: (2026)
A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning
by: Kang, Yan, et al.
Published: (2022)
by: Kang, Yan, et al.
Published: (2022)
Differential Privacy Analysis of Decentralized Gossip Averaging under Varying Threat Models
by: Koskela, Antti, et al.
Published: (2025)
by: Koskela, Antti, et al.
Published: (2025)
FedPDD: A Privacy-preserving Double Distillation Framework for Cross-silo Federated Recommendation
by: Wan, Sheng, et al.
Published: (2023)
by: Wan, Sheng, et al.
Published: (2023)
A Secure and Privacy-Friendly Logging Scheme
by: Aßmuth, Andreas, et al.
Published: (2024)
by: Aßmuth, Andreas, et al.
Published: (2024)
Lightweight Federated Learning with Differential Privacy and Straggler Resilience
by: Hong, Shu, et al.
Published: (2024)
by: Hong, Shu, et al.
Published: (2024)
zkFL-Health: Blockchain-Enabled Zero-Knowledge Federated Learning for Medical AI Privacy
by: Sharma, Savvy, et al.
Published: (2025)
by: Sharma, Savvy, et al.
Published: (2025)
Privacy-Enhanced Training-as-a-Service for On-Device Intelligence: Concept, Architectural Scheme, and Open Problems
by: Wu, Zhiyuan, et al.
Published: (2024)
by: Wu, Zhiyuan, et al.
Published: (2024)
Homomorphic Encryption in Healthcare Industry Applications for Protecting Data Privacy
by: Rauthan, J. S.
Published: (2025)
by: Rauthan, J. S.
Published: (2025)
Similar Items
-
Improving LoRA in Privacy-preserving Federated Learning
by: Sun, Youbang, et al.
Published: (2024) -
FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation
by: Xia, Tong, et al.
Published: (2023) -
Experimentally validated quantum-secure federated learning over a multi-user quantum network
by: Liu, Zhi-Ping, et al.
Published: (2025) -
PPFPL: Cross-silo Privacy-preserving Federated Prototype Learning Against Data Poisoning Attacks
by: Zhang, Hongliang, et al.
Published: (2025) -
A chaotic maps-based privacy-preserving distributed deep learning for incomplete and Non-IID datasets
by: Arévalo, Irina, et al.
Published: (2024)