BorjaBalle / amplification-by-shufflingLinks
Implementation of calibration bounds for differential privacy in the shuffle model
☆21Updated 4 years ago
Alternatives and similar repositories for amplification-by-shuffling
Users that are interested in amplification-by-shuffling are comparing it to the libraries listed below
Sorting:
- Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget☆49Updated 7 years ago
- An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawit…☆89Updated 6 years ago
- A sybil-resilient distributed learning protocol.☆104Updated last month
- IEEE TIFS'20: VeriFL: Communication-Efficient and Fast Verifiable Aggregation for Federated Learning☆25Updated 3 years ago
- Sample LDP implementation in Python☆129Updated 2 years ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆148Updated 3 years ago
- ☆35Updated 3 years ago
- A simple Python implementation of a secure aggregation protocole for federated learning.☆35Updated 2 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 is an implementation for paper "A Hybrid Approach to Privacy Preserving Federated Learning" (https://arxiv.org/pdf/1812.03224.pdf)☆23Updated 5 years ago
- Code for the paper "Bayesian Differential Privacy for Machine Learning"☆22Updated 5 years ago
- Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization☆12Updated 4 years ago
- Implementing the algorithm from our paper: "A Reputation Mechanism Is All You Need: Collaborative Fairness and Adversarial Robustness in …☆36Updated last year
- Code for the CCS'22 paper "Federated Boosted Decision Trees with Differential Privacy"☆49Updated 2 years ago
- Code for Data Poisoning Attacks Against Federated Learning Systems☆200Updated 4 years ago
- ☆28Updated 2 years ago
- Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470☆151Updated 3 years ago
- Differential private machine learning☆195Updated 3 years ago
- Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent (ICLR 2021)☆22Updated 4 years ago
- Code & supplementary material of the paper Label Inference Attacks Against Federated Learning on Usenix Security 2022.☆82Updated 2 years ago
- Differentially Private Federated Learning on Heterogeneous Data☆68Updated 3 years ago
- ⚔️ Blades: A Unified Benchmark Suite for Attacks and Defenses in Federated Learning☆148Updated 8 months ago
- DBA: Distributed Backdoor Attacks against Federated Learning (ICLR 2020)☆198Updated 4 years ago
- PyTorch implementation of Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance☆35Updated last year
- Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enfo…☆41Updated last year
- personal implementation of secure aggregation protocol☆45Updated last year
- ☆40Updated last year
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆49Updated 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
- The Algorithmic Foundations of Differential Pivacy by Cynthia Dwork Chinese Translation☆167Updated 2 years ago