ZhangIvan1 / Efficient-Privacy-Preserving-Federated-Learning-With-Improved-Compressed-SensingLinks
The source code of the paper "Efficient Privacy-Preserving Federated Learning with Compressed Sensing"
☆21Updated last year
Alternatives and similar repositories for Efficient-Privacy-Preserving-Federated-Learning-With-Improved-Compressed-Sensing
Users that are interested in Efficient-Privacy-Preserving-Federated-Learning-With-Improved-Compressed-Sensing are comparing it to the libraries listed below
Sorting:
- Differentially Private Federated Learning on Heterogeneous Data☆65Updated 3 years ago
- Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.☆45Updated 2 years ago
- Chain-PPFL: A Privacy-Preserving Federated Learning Framework based on Chained SMC☆35Updated 4 years ago
- Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.☆33Updated 4 years ago
- Local Differential Privacy for Federated Learning☆16Updated 2 years ago
- ☆41Updated last year
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…☆84Updated 2 years ago
- Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…☆42Updated 3 years ago
- This repository contains the official implementation for the manuscript: Make Landscape Flatter in Differentially Private Federated Lear…☆48Updated last year
- nips23-Dynamic Personalized Federated Learning with Adaptive Differential Privacy☆77Updated 9 months ago
- PyTorch implementation of Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance☆32Updated 8 months ago
- Implementation of Shuffled Model of Differential Privacy in Federated Learning." AISTATS, 2021.☆18Updated 2 years ago
- Implementing the algorithm from our paper: "A Reputation Mechanism Is All You Need: Collaborative Fairness and Adversarial Robustness in …☆35Updated last year
- ☆39Updated last year
- reproduce the FLTrust model based on the paper "FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping"☆29Updated 2 years ago
- Source code for MLSys 2022 submission "LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation in Federated Learning"☆23Updated 3 years ago
- Byzantine-robust Federated Learning☆16Updated last year
- ☆38Updated 4 years ago
- 基于《A Little Is Enough: Circumventing Defenses For Distributed Learning》的联邦学习攻击模型☆63Updated 5 years ago
- ☆18Updated 4 years ago
- Federated Learning and Membership Inference Attacks experiments on CIFAR10☆22Updated 5 years ago
- ☆15Updated last year
- ☆55Updated 2 years ago
- This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.☆45Updated 2 years ago
- ☆35Updated 3 years ago
- Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization☆11Updated 4 years ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆56Updated 2 years ago
- ☆36Updated 4 years ago
- ☆12Updated 2 years ago
- FedShare: Secure Aggregation based on Additive Secret Sharing in Federated Learning☆20Updated 2 years ago