Samuel-Maddock / pure-LDP
Python package for simple implementations of state-of-the-art LDP frequency estimation algorithms. Contains code for our VLDB 2021 Paper.
☆74Updated last year
Alternatives and similar repositories for pure-LDP:
Users that are interested in pure-LDP are comparing it to the libraries listed below
- Sample LDP implementation in Python☆122Updated last year
- Differential private machine learning☆190Updated 3 years ago
- Useful tools for differential privacy☆215Updated 2 years ago
- Multiple Frequency Estimation Under Local Differential Privacy in Python☆46Updated last year
- Code for the CCS'22 paper "Federated Boosted Decision Trees with Differential Privacy"☆44Updated last year
- Implementation of calibration bounds for differential privacy in the shuffle model☆23Updated 4 years ago
- ☆14Updated last week
- Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget☆49Updated 7 years ago
- Implementation of local differential privacy mechanisms in Python language.☆28Updated 2 years ago
- PyTorch implementation of a number of mechanisms in local differential privacy☆16Updated 3 years ago
- Secure and utility-aware data collection with condensed local differential privacy☆16Updated 4 years ago
- Implementation of dp-based federated learning framework using PyTorch☆294Updated last year
- Applying Laplace and exponential mechanisms to add random noise to data for differential privacy. Plotting MSE vs. epsilon.☆28Updated 4 years ago
- DPSUR☆24Updated last month
- Paper notes and code for differentially private machine learning☆347Updated 3 months ago
- ⚔️ Blades: A Unified Benchmark Suite for Attacks and Defenses in Federated Learning☆139Updated 2 weeks ago
- ☆33Updated 2 years ago
- FedAvg code with privacy protection function, the application of Paillier homomorphic encryption algorithm and differential privacy, diff…☆110Updated 5 months ago
- autodp: A flexible and easy-to-use package for differential privacy☆271Updated last year
- Curated notebooks on how to train neural networks using differential privacy and federated learning.☆66Updated 4 years ago
- Utility-aware synthesis of differentially private and attack-resilient location traces☆24Updated 6 years ago
- Preserve data privacy with k-anonymity (samarati & mondrian), differential privacy, federated learning, paillier homomorphic encryption, …☆58Updated 3 years ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆49Updated 3 years ago
- Privacy Preserving Vertical Federated Learning☆217Updated last year
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆130Updated 2 years ago
- An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawit…☆83Updated 5 years ago
- Differential Privacy Preservation in Deep Learning under Model Attacks☆132Updated 3 years ago
- Analytic calibration for differential privacy with Gaussian perturbations☆46Updated 6 years ago
- Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enfo…☆41Updated 10 months ago
- ☆305Updated last month