NBsyxx / privacy-preserving-machine-learning-with-hormomophic-encrypted-data
This project studied homomorphic encryption and attempted to apply it in training machine learning models. We trained some models on plain data and evaluated them on encrypted data using encrypted parameters. We eventually created a logistic regression model that trains on encrypted data and maintains high accuracy
☆11Updated 2 years ago
Related projects: ⓘ
- Privacy-Preserving Deep Learning via Additively Homomorphic Encryption☆66Updated 3 years ago
- Medical data is often highly sensitive in terms of data privacy and security concerns. Federated learning, one type of machine learn- ing…☆15Updated 2 years ago
- Multi‐key homomorphic encryption based on MKCKKS☆16Updated 2 years ago
- Privacy-Preserving Convolutional Neural Networks using Homomorphic Encryption☆69Updated last month
- SAFEFL: MPC-friendly Framework for Private and Robust Federated Learning☆28Updated last year
- MPC Secure Multiparty Computation. A three-party secret-sharing-based vertical federated learning setting. The data are vertically parti…☆24Updated 5 years ago
- Implementation of Privacy-Preserving Deep Learning via Additively Homomorphic Encryption (Using LWE schema)☆12Updated 6 years ago
- This repository provides python code for privacy preserving image classification based on fully homomorphic encryption (FHE).☆13Updated 5 years ago
- An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawit…☆80Updated 5 years ago
- Privacy-preserving federated learning is distributed machine learning where multiple collaborators train a model through protected gradi…☆26Updated 3 years ago
- [arXiv'21] Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning☆18Updated 8 months ago
- Secure Linear Regression in the Semi-Honest Two-Party Setting.☆36Updated 4 years ago
- Preserve data privacy with k-anonymity (samarati & mondrian), differential privacy, federated learning, paillier homomorphic encryption, …☆55Updated 2 years ago
- A mathematical and code introduction to the BFV Homomorphic Encryption scheme.☆33Updated last year
- ☆35Updated 9 months ago
- IEEE TIFS'20: VeriFL: Communication-Efficient and Fast Verifiable Aggregation for Federated Learning☆22Updated 2 years ago
- Repository for collection of research papers on multi-party learning.☆30Updated last year
- MPC team of Security Group in HITSZ☆19Updated 2 weeks ago
- Implementation of Shuffled Model of Differential Privacy in Federated Learning." AISTATS, 2021.☆17Updated last year
- Paper Notes in MPC with Applications to PPML☆65Updated 5 months ago
- Efficient and Straggler-Resistant Homomorphic Encryption for Heterogeneous Federated Learning☆12Updated 4 months ago
- A secure aggregation system for private federated learning☆32Updated 4 months ago
- Code for the CCS'22 paper "Federated Boosted Decision Trees with Differential Privacy"☆42Updated 11 months ago
- Chain-PPFL: A Privacy-Preserving Federated Learning Framework based on Chained SMC☆30Updated 4 years ago
- Secure Aggregation for FL☆34Updated 9 months ago
- This is an implementation for paper "A Hybrid Approach to Privacy Preserving Federated Learning" (https://arxiv.org/pdf/1812.03224.pdf)☆20Updated 4 years ago
- Privacy Preserving Federated Learning on a Deep Neural Network☆8Updated 4 years ago
- personal implementation of secure aggregation protocol☆41Updated 7 months ago
- ☆52Updated 2 years ago
- Implementation of calibration bounds for differential privacy in the shuffle model☆23Updated 3 years ago