shaneson0 / attacking_federate_learning
基于《A Little Is Enough: Circumventing Defenses For Distributed Learning》的联邦学习攻击模型
☆62Updated 4 years ago
Alternatives and similar repositories for attacking_federate_learning:
Users that are interested in attacking_federate_learning are comparing it to the libraries listed below
- ☆38Updated 3 years ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆142Updated 2 years ago
- ☆36Updated last year
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆71Updated 3 years ago
- ☆54Updated 2 years ago
- Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…☆39Updated 3 years ago
- ☆36Updated 3 years ago
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…☆75Updated 2 years ago
- A sybil-resilient distributed learning protocol.☆101Updated last year
- Official implementation of our work "Collaborative Fairness in Federated Learning."☆51Updated 9 months ago
- This repository contains the official implementation for the manuscript: Make Landscape Flatter in Differentially Private Federated Lear…☆47Updated last year
- This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.☆44Updated last year
- PyTorch implementation of Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance☆33Updated 5 months ago
- The code for "Improved Deep Leakage from Gradients" (iDLG).☆148Updated 4 years ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆55Updated last year
- ⚔️ Blades: A Unified Benchmark Suite for Attacks and Defenses in Federated Learning☆141Updated last month
- ☆69Updated 2 years ago
- Implementing the algorithm from our paper: "A Reputation Mechanism Is All You Need: Collaborative Fairness and Adversarial Robustness in …☆36Updated 9 months ago
- 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
- Differentially Private Federated Learning on Heterogeneous Data☆61Updated 3 years ago
- An implementation for the paper "A Little Is Enough: Circumventing Defenses For Distributed Learning" (NeurIPS 2019)☆26Updated last year
- A list of papers using/about Federated Learning especially malicious client and attacks.☆12Updated 4 years ago
- ☆36Updated 3 years ago
- nips23-Dynamic Personalized Federated Learning with Adaptive Differential Privacy☆64Updated 6 months ago
- code for TPDS paper "Towards Fair and Privacy-Preserving Federated Deep Models"☆31Updated 2 years ago
- Code & supplementary material of the paper Label Inference Attacks Against Federated Learning on Usenix Security 2022.☆83Updated last year
- Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.☆46Updated 2 years ago
- The code of the attack scheme in the paper "Backdoor Attack Against Split Neural Network-Based Vertical Federated Learning"☆17Updated last year
- An open source FL implement with dataset(Femnist, Shakespeare, MNIST, Cifar-10 and Fashion-Mnist) using pytorch☆122Updated last year
- DBA: Distributed Backdoor Attacks against Federated Learning (ICLR 2020)☆184Updated 3 years ago