sail-research / fed-unlearn
An Empirical Study of Federated Unlearning: Efficiency and Effectiveness (Accepted Conference Track Papers at ACML 2023)
☆16Updated last year
Alternatives and similar repositories for fed-unlearn:
Users that are interested in fed-unlearn are comparing it to the libraries listed below
- IBA: Towards Irreversible Backdoor Attacks in Federated Learning (Poster at NeurIPS 2023)☆33Updated last year
- Awesome Federated Unlearning (FU) Papers (Continually Update)☆88Updated 9 months ago
- Code implementation of the paper "Federated Unlearning: How to Efficiently Erase a Client in FL?" published at UpML (part of ICML 2022)☆33Updated 2 years ago
- ☆68Updated 2 years ago
- ☆38Updated 3 years ago
- ☆18Updated 4 years ago
- ☆10Updated last month
- Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…☆39Updated 3 years ago
- ☆25Updated last year
- ☆17Updated 2 years ago
- [ICML 2023] Official code implementation of "Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning (htt…☆38Updated last month
- ☆34Updated 3 years ago
- Papers related to federated learning in top conferences (2020-2024).☆67Updated 4 months ago
- [Usenix Security 2024] Official code implementation of "BackdoorIndicator: Leveraging OOD Data for Proactive Backdoor Detection in Federa…☆29Updated 4 months ago
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…☆74Updated last year
- ☆47Updated last year
- Adversarial attacks and defenses against federated learning.☆15Updated last year
- Github Repo for AAAI 2023 paper: On the Vulnerability of Backdoor Defenses for Federated Learning☆35Updated last year
- ☆12Updated last year
- This repository contains the official implementation for the manuscript: Make Landscape Flatter in Differentially Private Federated Lear…☆46Updated last year
- [ICLR 2023, Best Paper Award at ECCV’22 AROW Workshop] FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning☆52Updated 2 months ago
- PyTorch Implementation of Personalized federated learning with theoretical guarantees: A model-agnostic meta-learning approach☆47Updated 2 years ago
- ☆54Updated last year
- This is a simple backdoor model for federated learning.We use MNIST as the original data set for data attack and we use CIFAR-10 data set…☆14Updated 4 years ago
- ☆14Updated last year
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆55Updated last year
- ☆11Updated last year
- Official code for "Personalized Federated Learning through Local Memorization" (ICML'22)☆43Updated last year
- ☆18Updated last year
- PyTorch implementation of Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance☆33Updated 4 months ago