Alternatives and similar repositories for Deep-Learning-with-GDP-Pytorch

Users that are interested in Deep-Learning-with-GDP-Pytorch are comparing it to the libraries listed below

• woodyx218 / Deep-Learning-with-GDP-Tensorflow
  Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"
  ☆49Updated 4 years ago
• dayu11 / Differentially-Private-Deep-Learning
  This repo implements several algorithms for learning with differential privacy.
  ☆108Updated 2 years ago
• jeremy313 / Soteria
  Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"
  ☆57Updated 2 years ago
• krishnap25 / RFA
  Robust aggregation for federated learning with the RFA algorithm.
  ☆48Updated 2 years ago
• maxencenoble / Differential-Privacy-for-Heterogeneous-Federated-Learning
  Differentially Private Federated Learning on Heterogeneous Data
  ☆66Updated 3 years ago
• AI-secure / CRFL
  CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)
  ☆73Updated 3 years ago
• PatrickZH / Improved-Deep-Leakage-from-Gradients
  The code for "Improved Deep Leakage from Gradients" (iDLG).
  ☆152Updated 4 years ago
• shrebox / Privacy-Attacks-in-Machine-Learning
  Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.
  ☆62Updated 9 months ago
• git-disl / CPL_attack
  ☆37Updated 3 years ago
• s-huu / Ditto
  ☆54Updated 4 years ago
• inspire-group / ModelPoisoning
  Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470
  ☆151Updated 2 years ago
• shaneson0 / attacking_federate_learning
  基于《A Little Is Enough: Circumventing Defenses For Distributed Learning》的联邦学习攻击模型
  ☆63Updated 5 years ago
• zaixizhang / FLDetector
  The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…
  ☆84Updated 2 years ago
• papersdclub / Differentially_private_federated_learning
  Differentially Private Federated Learning: A Client Level Perspective
  ☆12Updated 6 years ago
• pasquini-dario / SplitNN_FSHA
  Privacy attacks on Split Learning
  ☆42Updated 3 years ago
• lingjuanlv / FPPDL
  code for TPDS paper "Towards Fair and Privacy-Preserving Federated Deep Models"
  ☆31Updated 3 years ago
• FumiyukiKato / FL-attacks-papers
  A list of papers using/about Federated Learning especially malicious client and attacks.
  ☆12Updated 4 years ago
• epfml / byzantine-robust-optimizer
  Learning from history for Byzantine Robustness
  ☆23Updated 4 years ago
• AdrienBenamira / membership_inference_attack
  Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.
  ☆60Updated 6 years ago
• vrt1shjwlkr / NDSS21-Model-Poisoning
  Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"
  ☆147Updated 2 years ago
• ksreenivasan / OOD_Federated_Learning
  ☆70Updated 3 years ago
• PengchaoHan / Adaptive_Gradient_Sparsification_FL
  Adaptive gradient sparsification for efficient federated learning: an online learning approach
  ☆18Updated 4 years ago
• thecml / dpsgd-optimizer
  Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enfo…
  ☆41Updated last year
• AI-secure / DBA
  DBA: Distributed Backdoor Attacks against Federated Learning (ICLR 2020)
  ☆196Updated 3 years ago
• haiphanNJIT / PrivateDeepLearning
  Differential Privacy Preservation in Deep Learning under Model Attacks
  ☆135Updated 4 years ago
• DPBayes / ADADP
  Learning rate adaptation for differentially private stochastic gradient descent
  ☆16Updated 4 years ago
• bargavj / EvaluatingDPML
  This project's goal is to evaluate the privacy leakage of differentially private machine learning models.
  ☆135Updated 2 years ago
• ebagdasa / federated_adaptation
  Salvaging Federated Learning by Local Adaptation
  ☆56Updated 11 months ago
• jgshu / Attacks-and-Defenses-in-Federated-Learning
  ☆38Updated 4 years ago
• AlekseiTriastcyn / bayesian-differential-privacy
  Code for the paper "Bayesian Differential Privacy for Machine Learning"
  ☆22Updated 4 years ago