loretanr / dp-gbdtLinks
GBDT learning + differential privacy. Standalone C++ implementation of "DPBoost" (Li et al.). There are further hardened & SGX versions of the code.
☆8Updated 3 years ago
Alternatives and similar repositories for dp-gbdt
Users that are interested in dp-gbdt are comparing it to the libraries listed below
Sorting:
- A simple Python implementation of a secure aggregation protocole for federated learning.☆35Updated 2 years ago
- Implementation of calibration bounds for differential privacy in the shuffle model☆22Updated 4 years ago
- ☆9Updated 3 years ago
- An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawit…☆88Updated 5 years ago
- IEEE TIFS'20: VeriFL: Communication-Efficient and Fast Verifiable Aggregation for Federated Learning☆24Updated 2 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 2 years ago
- Sample LDP implementation in Python☆129Updated last year
- Privacy-Preserving Deep Learning via Additively Homomorphic Encryption☆70Updated 4 years ago
- Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget☆49Updated 7 years ago
- Code for Data Poisoning Attacks Against Federated Learning Systems☆195Updated 4 years ago
- Differential Privacy Preservation in Deep Learning under Model Attacks☆135Updated 4 years ago
- FedAvg code with privacy protection function, the application of Paillier homomorphic encryption algorithm and differential privacy, diff…☆122Updated 9 months ago
- Analytic calibration for differential privacy with Gaussian perturbations☆48Updated 6 years ago
- Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)☆194Updated 7 years ago
- A secure aggregation system for private federated learning☆41Updated last year
- autodp: A flexible and easy-to-use package for differential privacy☆273Updated last year
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆49Updated 4 years ago
- Unified, Simplified, Tight and Fast Privacy Amplification in the Shuffle Model of Differential Privacy☆11Updated 8 months ago
- Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enfo…☆40Updated last year
- Source code for paper "How to Backdoor Federated Learning" (https://arxiv.org/abs/1807.00459)☆299Updated 11 months ago
- MPC Secure Multiparty Computation. A three-party secret-sharing-based vertical federated learning setting. The data are vertically parti…☆23Updated 6 years ago
- personal implementation of secure aggregation protocol☆46Updated last year
- An implementation of Deep Learning with Differential Privacy☆25Updated 2 years ago
- Privacy Preserving Vertical Federated Learning☆218Updated 2 years ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆147Updated 2 years ago
- reproduce the FLTrust model based on the paper "FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping"☆30Updated 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
- FedShare: Secure Aggregation based on Additive Secret Sharing in Federated Learning☆20Updated 2 years ago
- ☆28Updated 2 years ago
- SAFEFL: MPC-friendly Framework for Private and Robust Federated Learning☆39Updated last year