wangsw / PrivacyAmplificationLinks
Unified, Simplified, Tight and Fast Privacy Amplification in the Shuffle Model of Differential Privacy
☆11Updated 10 months ago
Alternatives and similar repositories for PrivacyAmplification
Users that are interested in PrivacyAmplification are comparing it to the libraries listed below
Sorting:
- An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawit…☆89Updated 6 years ago
- Materials about Privacy-Preserving Machine Learning☆257Updated last week
- Sample LDP implementation in Python☆129Updated 2 years ago
- IEEE TIFS'20: VeriFL: Communication-Efficient and Fast Verifiable Aggregation for Federated Learning☆25Updated 3 years ago
- Repository for collection of research papers on multi-party learning.☆33Updated 2 years ago
- Paper Notes in MPC with Applications to PPML☆71Updated last year
- Code repository for the paper at USENIX Security'24☆32Updated last year
- Multiple Frequency Estimation Under Local Differential Privacy in Python☆49Updated 2 years ago
- ☆37Updated 10 months ago
- A simple Python implementation of a secure aggregation protocole for federated learning.☆35Updated 2 years ago
- personal implementation of secure aggregation protocol☆46Updated last year
- The Algorithmic Foundations of Differential Pivacy by Cynthia Dwork Chinese Translation☆165Updated 2 years ago
- Python package for simple implementations of state-of-the-art LDP frequency estimation algorithms. Contains code for our VLDB 2021 Paper.☆76Updated 2 years ago
- Implementation of calibration bounds for differential privacy in the shuffle model☆22Updated 4 years ago
- Secure Linear Regression in the Semi-Honest Two-Party Setting.☆38Updated 5 years ago
- SAFEFL: MPC-friendly Framework for Private and Robust Federated Learning☆42Updated 2 years ago
- Implementation of protocols in Falcon☆95Updated last year
- Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing☆51Updated 4 years ago
- Multi‐key homomorphic encryption based on MKCKKS☆20Updated 3 years ago
- The repo of "BumbleBee: Secure Two-party Inference Framework for Large Transformers" (NDSS 2025)☆44Updated 7 months ago
- Implementation of local differential privacy mechanisms in Python language.☆29Updated 3 years ago
- FudanMPL 2.0, a series of multi-party learning frameworks, with rich features, including secure and fast XGBoost, secure Fine-tuning for …☆51Updated last month
- Medical data is often highly sensitive in terms of data privacy and security concerns. Federated learning, one type of machine learn- ing…☆23Updated 3 years ago
- Code for the CCS'22 paper "Federated Boosted Decision Trees with Differential Privacy"☆46Updated last year
- ☆16Updated 11 months ago
- MCSI☆13Updated 3 years ago
- A secure aggregation system for private federated learning☆41Updated last year
- Privacy-preserving federated learning is distributed machine learning where multiple collaborators train a model through protected gradi…☆31Updated 4 years ago
- Homomorphic Encryption and Federated Learning based Privacy-Preserving☆72Updated 2 years ago
- [INFOCOM24' & TDSC25']FedPHE & Efficient and Straggler-Resistant Homomorphic Encryption for Heterogeneous Federated Learning☆36Updated 3 weeks ago