thecml / dpsgd-optimizerLinks
Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enforces privacy by clipping and sanitising the gradients with Gaussian noise during training.
☆41Updated last year
Alternatives and similar repositories for dpsgd-optimizer
Users that are interested in dpsgd-optimizer are comparing it to the libraries listed below
Sorting:
- Code for Data Poisoning Attacks Against Federated Learning Systems☆200Updated 4 years ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆148Updated 3 years ago
- Implementation of dp-based federated learning framework using PyTorch☆310Updated 2 years ago
- Curated notebooks on how to train neural networks using differential privacy and federated learning.☆67Updated 4 years ago
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…☆84Updated 2 years ago
- A sybil-resilient distributed learning protocol.☆104Updated last month
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆57Updated 2 years ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆49Updated 4 years ago
- Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.☆64Updated last year
- PyTorch implementation of Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance☆35Updated last year
- Implementation of calibration bounds for differential privacy in the shuffle model☆21Updated 4 years ago
- Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget☆49Updated 7 years ago
- Ditto: Fair and Robust Federated Learning Through Personalization (ICML '21)☆148Updated 3 years ago
- Differential private machine learning☆195Updated 3 years ago
- This repository contains the official implementation for the manuscript: Make Landscape Flatter in Differentially Private Federated Lear…☆54Updated 2 weeks ago
- An open source FL implement with dataset(Femnist, Shakespeare, MNIST, Cifar-10 and Fashion-Mnist) using pytorch☆132Updated 2 years ago
- Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470☆151Updated 3 years ago
- ☆43Updated 2 years ago
- ☆38Updated 4 years ago
- This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.☆45Updated 2 years ago
- This repo implements several algorithms for learning with differential privacy.☆109Updated 2 years ago
- ☆35Updated 3 years ago
- Code for the CCS'22 paper "Federated Boosted Decision Trees with Differential Privacy"☆49Updated 2 years ago
- ☆22Updated 2 years ago
- Adversarial attacks and defenses against federated learning.☆20Updated 2 years ago
- ⚔️ Blades: A Unified Benchmark Suite for Attacks and Defenses in Federated Learning☆148Updated 8 months ago
- Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.☆46Updated 2 years ago
- ☆54Updated 4 years ago
- Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.☆33Updated 4 years ago
- Algorithms to recover input data from their gradient signal through a neural network☆305Updated 2 years ago