Alternatives and similar repositories for DP-FTRL

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

• facebookresearch / dp_compression
  Code repo for the paper "Privacy-aware Compression for Federated Data Analysis".
  ☆19Updated 2 years ago
• google-research / public-data-in-dpfl
  ☆22Updated 2 years ago
• woodyx218 / opacus_global_clipping
  ☆15Updated 2 years ago
• jeremy313 / Soteria
  Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"
  ☆56Updated 2 years ago
• AI-secure / CRFL
  CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)
  ☆72Updated 3 years ago
• dayu11 / Gradient-Embedding-Perturbation
  ☆27Updated 2 years ago
• pasquini-dario / SplitNN_FSHA
  Privacy attacks on Split Learning
  ☆42Updated 3 years ago
• awslabs / fast-differential-privacy
  Fast, memory-efficient, scalable optimization of deep learning with differential privacy
  ☆121Updated last month
• dayu11 / Differentially-Private-Deep-Learning
  This repo implements several algorithms for learning with differential privacy.
  ☆108Updated 2 years ago
• microsoft / prv_accountant
  A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.
  ☆73Updated last year
• pps-lab / rofl-project-code
  ☆32Updated 2 years ago
• AI-secure / FLBenchmark-toolkit
  Federated Learning Framework Benchmark (UniFed)
  ☆49Updated 2 years ago
• AI-secure / DataLens
  [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…
  ☆38Updated 3 years ago
• sam-yeom / ml-privacy-csf18
  Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"
  ☆37Updated 6 years ago
• bargavj / EvaluatingDPML
  This project's goal is to evaluate the privacy leakage of differentially private machine learning models.
  ☆135Updated 2 years ago
• facebookresearch / label_dp_antipodes
  Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"
  ☆32Updated 3 years ago
• spliew / shuffgauss
  ☆10Updated last year
• google-deepmind / jax_privacy
  Algorithms for Privacy-Preserving Machine Learning in JAX
  ☆94Updated 2 months ago
• Samuel-Maddock / federated-boosted-dp-trees
  Code for the CCS'22 paper "Federated Boosted Decision Trees with Differential Privacy"
  ☆46Updated last year
• krishnap25 / simplicial-fl
  Simplicial-FL to manage client device heterogeneity in Federated Learning
  ☆22Updated last year
• BielStela / membership_inference
  Python package to create adversarial agents for membership inference attacks againts machine learning models
  ☆47Updated 6 years ago
• zechenghe / Inverse_Collaborative_Inference
  ☆45Updated 3 years ago
• AdrienBenamira / membership_inference_attack
  Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.
  ☆60Updated 6 years ago
• PatrickZH / Improved-Deep-Leakage-from-Gradients
  The code for "Improved Deep Leakage from Gradients" (iDLG).
  ☆152Updated 4 years ago
• wanglun1996 / secure-robust-federated-learning
  ☆55Updated 2 years ago
• Machine-Learning-Security-Lab / mia_prune
  Membership Inference Attacks and Defenses in Neural Network Pruning
  ☆28Updated 2 years ago
• woodyx218 / Deep-Learning-with-GDP-Pytorch
  Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"
  ☆33Updated 4 years ago
• jagielski / auditing-dpsgd
  Code for Auditing DPSGD
  ☆37Updated 3 years ago
• DingfanChen / RelaxLoss
  Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)
  ☆50Updated 2 years ago
• shrebox / Privacy-Attacks-in-Machine-Learning
  Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.
  ☆62Updated 8 months ago