hwang595 / DETOX
DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation
☆16Updated 4 years ago
Alternatives and similar repositories for DETOX:
Users that are interested in DETOX are comparing it to the libraries listed below
- ☆15Updated 5 years ago
- An implementation for the paper "A Little Is Enough: Circumventing Defenses For Distributed Learning" (NeurIPS 2019)☆26Updated last year
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆71Updated 3 years ago
- ☆31Updated 4 years ago
- code for TPDS paper "Towards Fair and Privacy-Preserving Federated Deep Models"☆31Updated 2 years ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆31Updated 3 years ago
- A list of papers using/about Federated Learning especially malicious client and attacks.☆12Updated 4 years ago
- Simplicial-FL to manage client device heterogeneity in Federated Learning☆22Updated last year
- ☆41Updated 9 months ago
- ☆21Updated 3 years ago
- ☆54Updated 2 years ago
- 基于《A Little Is Enough: Circumventing Defenses For Distributed Learning》的联邦学习攻击模型☆62Updated 4 years ago
- Salvaging Federated Learning by Local Adaptation☆56Updated 6 months ago
- Learning from history for Byzantine Robustness☆22Updated 3 years ago
- Official implementation of our work "Collaborative Fairness in Federated Learning."☆50Updated 8 months ago
- ☆18Updated 4 years ago
- This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.☆44Updated last year
- ☆54Updated 3 years ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆55Updated last year
- ☆13Updated last year
- ☆38Updated 3 years ago
- Code for paper "Byzantine-Resilient Distributed Finite-Sum Optimization over Networks"☆18Updated 4 years ago
- FedDANE: A Federated Newton-Type Method (Asilomar Conference on Signals, Systems, and Computers ‘19)☆25Updated last year
- Robust aggregation for federated learning with the RFA algorithm.☆47Updated 2 years ago
- ☆14Updated last year
- simple Differential Privacy in PyTorch☆48Updated 4 years ago
- [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…☆37Updated 3 years ago
- Privacy attacks on Split Learning☆37Updated 3 years ago
- Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent (ICLR 2021)☆20Updated 3 years ago
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…☆74Updated last year