Alternatives and similar repositories for DP-FedSAM

Users that are interested in DP-FedSAM are comparing it to the libraries listed below

• zhmzm / FLTrust_pytorch
  ☆39Updated last year
• zaixizhang / FLDetector
  The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…
  ☆84Updated 2 years ago
• jeremy313 / FL-WBC
  Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…
  ☆42Updated 3 years ago
• vrt1shjwlkr / NDSS21-Model-Poisoning
  Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"
  ☆147Updated 3 years ago
• maxencenoble / Differential-Privacy-for-Heterogeneous-Federated-Learning
  Differentially Private Federated Learning on Heterogeneous Data
  ☆66Updated 3 years ago
• xiyuanyang45 / DynamicPFL
  nips23-Dynamic Personalized Federated Learning with Adaptive Differential Privacy
  ☆81Updated 11 months ago
• wenzhu23333 / Federated-Learning
  An open source FL implement with dataset(Femnist, Shakespeare, MNIST, Cifar-10 and Fashion-Mnist) using pytorch
  ☆130Updated 2 years ago
• lishenghui / blades
  ⚔️ Blades: A Unified Benchmark Suite for Attacks and Defenses in Federated Learning
  ☆143Updated 6 months ago
• BHui97 / PrivateFL
  ☆42Updated 2 years ago
• XinyiYS / Robust-and-Fair-Federated-Learning
  Implementing the algorithm from our paper: "A Reputation Mechanism Is All You Need: Collaborative Fairness and Adversarial Robustness in …
  ☆35Updated last year
• JiyaSu / ourFLTrust
  reproduce the FLTrust model based on the paper "FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping"
  ☆30Updated 2 years ago
• jgshu / Attacks-and-Defenses-in-Federated-Learning
  ☆39Updated 4 years ago
• yjlee22 / byzantineFL
  PyTorch implementation of Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance
  ☆34Updated 10 months ago
• Accenture / Labs-Federated-Learning
  Accenture Labs Federated Learning
  ☆104Updated last year
• BapFL / code
  Implementation of BapFL: You can Backdoor Attack Personalized Federated Learning
  ☆14Updated last year
• litian96 / ditto
  Ditto: Fair and Robust Federated Learning Through Personalization (ICML '21)
  ☆145Updated 3 years ago
• AdamWei-boop / Federated-Learning-with-Local-Differential-Privacy
  Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.
  ☆45Updated 2 years ago
• cpwan / Attack-Adaptive-Aggregation-in-Federated-Learning
  This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.
  ☆45Updated 2 years ago
• XinyiYS / CollaborativeFairFederatedLearning
  Official implementation of our work "Collaborative Fairness in Federated Learning."
  ☆54Updated last year
• JianXu95 / SignGuard
  ☆14Updated 2 years ago
• rong-dai / DisPFL
  [ICML 2022] "DisPFL: Towards Communication-Efficient Personalized Federated learning via Decentralized Sparse Training"
  ☆82Updated 3 years ago
• felisat / clustered-federated-learning
  Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints
  ☆174Updated 4 years ago
• git-disl / DataPoisoning_FL
  Code for Data Poisoning Attacks Against Federated Learning Systems
  ☆197Updated 4 years ago
• ehsanul9511 / FLShield
  ☆16Updated last year
• TinfoilHat0 / Defending-Against-Backdoors-with-Robust-Learning-Rate
  The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".
  ☆34Updated 2 years ago
• jichan3751 / ifca
  Codebase for An Efficient Framework for Clustered Federated Learning.
  ☆116Updated 4 years ago
• alpemreacar / FedDyn
  ☆77Updated 3 years ago
• jeremy313 / Soteria
  Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"
  ☆57Updated 2 years ago
• lebyni / PFA
  ☆35Updated 4 years ago
• AIoT-MLSys-Lab / FedRolex
  [NeurIPS 2022] "FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction" by Samiul Alam, Luyang Liu, Ming Yan,…
  ☆64Updated 11 months ago