Cover Image

Private Federated Learning In Real World Application -- A Case Study

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ji, An, Bandyopadhyay, Bortik, Song, Congzheng, Krishnaswami, Natarajan, Vashisht, Prabal, Smiroldo, Rigel, Litton, Isabel, Mahinder, Sayantan, Chitnis, Mona, Hill, Andrew W
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

pfl-research: simulation framework for accelerating research in Private Federated Learning
by: Granqvist, Filip, et al.
Published: (2024)

Applying RLAIF for Code Generation with API-usage in Lightweight LLMs
by: Dutta, Sujan, et al.
Published: (2024)

Momentum Approximation in Asynchronous Private Federated Learning
by: Yu, Tao, et al.
Published: (2024)

Samplable Anonymous Aggregation for Private Federated Data Analysis
by: Talwar, Kunal, et al.
Published: (2023)

Retrieval Augmented Correction of Named Entity Speech Recognition Errors
by: Pusateri, Ernest, et al.
Published: (2024)

CriteoPrivateAds: A Real-World Bidding Dataset to Design Private Advertising Systems
by: Sebbar, Mehdi, et al.
Published: (2025)

Enhancing Privacy in Federated Learning: Secure Aggregation for Real-World Healthcare Applications
by: Taiello, Riccardo, et al.
Published: (2024)

FederBoost: Private Federated Learning for GBDT
by: Tian, Zhihua, et al.
Published: (2020)

Cyclic Adaptive Private Synthesis for Sharing Real-World Data in Education
by: Ito, Hibiki, et al.
Published: (2026)

Secure Stateful Aggregation: A Practical Protocol with Applications in Differentially-Private Federated Learning
by: Ball, Marshall, et al.
Published: (2024)

Lightweight Security for Private Networks: Real-World Evaluation of WireGuard
by: Djuitcheu, Hubert, et al.
Published: (2025)

Flamingo: Multi-Round Single-Server Secure Aggregation with Applications to Private Federated Learning
by: Ma, Yiping, et al.
Published: (2023)

Private Stochastic Optimization With Large Worst-Case Lipschitz Parameter
by: Lowy, Andrew, et al.
Published: (2022)

Private and Communication-Efficient Federated Learning based on Differentially Private Sketches
by: Zhang, Meifan, et al.
Published: (2024)

Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses
by: Lowy, Andrew, et al.
Published: (2021)

Paladin: A Policy Framework for Securing Cloud APIs by Combining Application Context with Generative AI
by: Priya, Shriti, et al.
Published: (2026)

Bilateral Differentially Private Vertical Federated Boosted Decision Trees
by: Zhang, Bokang, et al.
Published: (2025)

MAUI: Reconstructing Private Client Data in Federated Transfer Learning
by: Dabholkar, Ahaan, et al.
Published: (2025)

Improving Parameter-Efficient Federated Learning with Differentially Private Refactorization
by: Tran, Linh, et al.
Published: (2026)

Design and Performance Evaluation of a BLE-Based IoT Authentication System
by: Yadav, Nitesh, et al.
Published: (2026)

Zero Day Malware Detection with Alpha: Fast DBI with Transformer Models for Real World Application
by: Gaber, Matthew, et al.
Published: (2025)

Private Data Leakage in Federated Human Activity Recognition for Wearable Healthcare Devices
by: Chen, Kongyang, et al.
Published: (2024)

DP-BREM: Differentially-Private and Byzantine-Robust Federated Learning with Client Momentum
by: Gu, Xiaolan, et al.
Published: (2023)

Harnessing Sparsification in Federated Learning: A Secure, Efficient, and Differentially Private Realization
by: Xu, Shuangqing, et al.
Published: (2025)

Compressed Private Aggregation for Scalable and Robust Federated Learning over Massive Networks
by: Lang, Natalie, et al.
Published: (2023)

Efficient Full-Stack Private Federated Deep Learning with Post-Quantum Security
by: Zhang, Yiwei, et al.
Published: (2025)

Differentially Private Federated Learning: A Systematic Review
by: Fu, Jie, et al.
Published: (2024)

Differential Private Federated Transfer Learning for Mental Health Monitoring in Everyday Settings: A Case Study on Stress Detection
by: Wang, Ziyu, et al.
Published: (2024)

SIMD-Aware Homomorphic Compression and Application to Private Database Query
by: Cheon, Jung Hee, et al.
Published: (2024)

How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study
by: Mitic, Natalija, et al.
Published: (2024)

HeteroFedSyn: Differentially Private Tabular Data Synthesis for Heterogeneous Federated Settings
by: Li, Xiaochen, et al.
Published: (2026)

DictPFL: Efficient and Private Federated Learning on Encrypted Gradients
by: Xue, Jiaqi, et al.
Published: (2025)

Fluent: Round-efficient Secure Aggregation for Private Federated Learning
by: Li, Xincheng, et al.
Published: (2024)

Inferentially-Private Private Information
by: Wang, Shuaiqi, et al.
Published: (2024)

Exploration on Real World Assets and Tokenization
by: Xia, Ning, et al.
Published: (2025)

A Robust Framework for Secure Cardiovascular Risk Prediction: An Architectural Case Study of Differentially Private Federated Learning
by: Tertulino, Rodrigo, et al.
Published: (2026)

A Comprehensive Survey of Threshold Signatures: NIST Standards, Post-Quantum Cryptography, Exotic Techniques, and Real-World Applications
by: Sedghighadikolaei, Kiarash, et al.
Published: (2023)

Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix
by: Wen, Ming, et al.
Published: (2025)

Differentially Private Federated $k$-Means Clustering with Server-Side Data
by: Scott, Jonathan, et al.
Published: (2025)

Differentially Private Federated Learning without Noise Addition: When is it Possible?
by: Zhang, Jiang, et al.
Published: (2024)