Cover Image

Comments on "Federated Learning with Differential Privacy: Algorithms and Performance Analysis"

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Talaei, Mahtab, Izadi, Iman
Format:	Preprint
Published:	2024
Subjects:	Distributed, Parallel, and Cluster Computing Cryptography and Security Performance
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adaptive Differential Privacy in Federated Learning: A Priority-Based Approach
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)

SoK: Concurrency in Blockchain -- A Systematic Literature Review and the Unveiling of a Misconception
by: Chahoki, Atefeh Zareh, et al.
Published: (2025)

Lightweight Federated Learning with Differential Privacy and Straggler Resilience
by: Hong, Shu, et al.
Published: (2024)

ZKProphet: Understanding Performance of Zero-Knowledge Proofs on GPUs
by: Verma, Tarunesh, et al.
Published: (2025)

Adversarial Analysis of the Differentially-Private Federated Learning in Cyber-Physical Critical Infrastructures
by: Hossain, Md Tamjid, et al.
Published: (2022)

On Fair Ordering and Differential Privacy
by: Cohen, Shir, et al.
Published: (2025)

Differential Privacy for Secure Machine Learning in Healthcare IoT-Cloud Systems
by: Mangala, N, et al.
Published: (2025)

An Adaptive Differential Privacy Method Based on Federated Learning
by: Wang, Zhiqiang, et al.
Published: (2024)

Advances in Privacy Preserving Federated Learning to Realize a Truly Learning Healthcare System
by: Madduri, Ravi, et al.
Published: (2024)

Privacy-First Crowdsourcing: Blockchain and Local Differential Privacy in Crowdsourced Drone Services
by: Akram, Junaid, et al.
Published: (2024)

Quantum-Inspired Privacy-Preserving Federated Learning Framework for Secure Dementia Classification
by: Tanbhir, Gazi, et al.
Published: (2025)

Evaluating the Potential of In-Memory Processing to Accelerate Homomorphic Encryption
by: Mwaisela, Mpoki, et al.
Published: (2024)

Exploiting Unstructured Sparsity in Fully Homomorphic Encrypted DNNs
by: Ferguson, Aidan, et al.
Published: (2025)

Design and implementation of a distributed security threat detection system integrating federated learning and multimodal LLM
by: Wang, Yuqing, et al.
Published: (2025)

Differentially Private Federated Learning With Time-Adaptive Privacy Spending
by: Kiani, Shahrzad, et al.
Published: (2025)

PPFPL: Cross-silo Privacy-preserving Federated Prototype Learning Against Data Poisoning Attacks
by: Zhang, Hongliang, et al.
Published: (2025)

The Effect of Quantization in Federated Learning: A Rényi Differential Privacy Perspective
by: Kang, Tianqu, et al.
Published: (2024)

Lancelot: Towards Efficient and Privacy-Preserving Byzantine-Robust Federated Learning within Fully Homomorphic Encryption
by: Jiang, Siyang, et al.
Published: (2024)

DP2Guard: A Lightweight and Byzantine-Robust Privacy-Preserving Federated Learning Scheme for Industrial IoT
by: Han, Baofu, et al.
Published: (2025)

Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning
by: Malekmohammadi, Saber, et al.
Published: (2024)

Privacy-Preserving Data Processing in Cloud : From Homomorphic Encryption to Federated Analytics
by: Sarraf, Gaurav, et al.
Published: (2026)

Performance Evaluation of Hashing Algorithms on Commodity Hardware
by: Pandya, Marut
Published: (2024)

PPVF: An Efficient Privacy-Preserving Online Video Fetching Framework with Correlated Differential Privacy
by: Zhang, Xianzhi, et al.
Published: (2024)

HHEML: Hybrid Homomorphic Encryption for Privacy-Preserving Machine Learning on Edge
by: Chan, Yu Hin, et al.
Published: (2025)

Trustworthy Federated Learning: Privacy, Security, and Beyond
by: Chen, Chunlu, et al.
Published: (2024)

Secure and Privacy-Preserving Vertical Federated Learning
by: Jin, Shan, et al.
Published: (2026)

Differentially Private Clustered Federated Learning
by: Malekmohammadi, Saber, et al.
Published: (2024)

Split Learning without Local Weight Sharing to Enhance Client-side Data Privacy
by: Pham, Ngoc Duy, et al.
Published: (2022)

HERL: Tiered Federated Learning with Adaptive Homomorphic Encryption using Reinforcement Learning
by: Tang, Jiaxang, et al.
Published: (2024)

No Vandalism: Privacy-Preserving and Byzantine-Robust Federated Learning
by: Xing, Zhibo, et al.
Published: (2024)

Improving LoRA in Privacy-preserving Federated Learning
by: Sun, Youbang, et al.
Published: (2024)

Fantastyc: Blockchain-based Federated Learning Made Secure and Practical
by: Boitier, William, et al.
Published: (2024)

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning
by: Zhao, Zhihui, et al.
Published: (2025)

DarkFed: A Data-Free Backdoor Attack in Federated Learning
by: Li, Minghui, et al.
Published: (2024)

When Quantum Federated Learning Meets Blockchain in 6G Networks
by: Nguyen, Dinh C., et al.
Published: (2025)

Zero-Knowledge Proof-Based Consensus for Blockchain-Secured Federated Learning
by: Fu, Tianxing, et al.
Published: (2025)

Differentially-Private Multi-Tier Federated Learning
by: Chen, Evan, et al.
Published: (2024)

Share Secrets for Privacy: Confidential Forecasting with Vertical Federated Learning
by: Shankar, Aditya, et al.
Published: (2024)

Practical Framework for Privacy-Preserving and Byzantine-robust Federated Learning
by: Zhang, Baolei, et al.
Published: (2025)