abogdanova / FL-MIALinks
Federated Learning and Membership Inference Attacks experiments on CIFAR10
☆23Updated 5 years ago
Alternatives and similar repositories for FL-MIA
Users that are interested in FL-MIA are comparing it to the libraries listed below
Sorting:
- Differentially Private Federated Learning on Heterogeneous Data☆70Updated 3 years ago
- PyTorch implementation of Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance☆34Updated last year
- Membership Inference Attack on Federated Learning☆12Updated 3 years ago
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…☆84Updated 2 years ago
- Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.☆46Updated 3 years ago
- Chain-PPFL: A Privacy-Preserving Federated Learning Framework based on Chained SMC☆37Updated 5 years ago
- ☆24Updated 3 years ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆148Updated 3 years ago
- A sybil-resilient distributed learning protocol.☆107Updated 3 months ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆57Updated 2 years ago
- This repository contains the official implementation for the manuscript: Make Landscape Flatter in Differentially Private Federated Lear…☆56Updated 2 months ago
- Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.☆35Updated 4 years ago
- Differentially Private Federated Learning: A Client Level Perspective☆12Updated 6 years ago
- ☆46Updated 2 years ago
- Implementing the algorithm from our paper: "A Reputation Mechanism Is All You Need: Collaborative Fairness and Adversarial Robustness in …☆38Updated last year
- ☆15Updated 2 years ago
- Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…☆44Updated 4 years ago
- Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization☆13Updated 4 years ago
- This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.☆46Updated 2 years ago
- ⚔️ Blades: A Unified Benchmark Suite for Attacks and Defenses in Federated Learning☆153Updated 10 months ago
- Code & supplementary material of the paper Label Inference Attacks Against Federated Learning on Usenix Security 2022.☆87Updated 2 years ago
- This is the repository for the work "An ensemble mechanism to tackle the heterogeneity in asynchronous federated learning"☆11Updated 4 years ago
- ☆39Updated last year
- Official implementation of our work "Collaborative Fairness in Federated Learning."☆54Updated last year
- Source code for MLSys 2022 submission "LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation in Federated Learning"☆24Updated 4 years ago
- Eluding Secure Aggregation in Federated Learning via Model Inconsistency☆12Updated 2 years ago
- Code for Data Poisoning Attacks Against Federated Learning Systems☆205Updated 4 years ago
- Adversarial attacks and defenses against federated learning.☆20Updated 2 years ago
- Local Differential Privacy for Federated Learning☆19Updated 3 years ago
- ☆19Updated 5 years ago