kjam / practical-data-privacyLinks
Practical Data Privacy
☆96Updated 10 months ago
Alternatives and similar repositories for practical-data-privacy
Users that are interested in practical-data-privacy are comparing it to the libraries listed below
Sorting:
- A toolkit for tools and techniques related to the privacy and compliance of AI models.☆105Updated 2 months ago
- Tools and service for differentially private processing of tabular and relational data☆273Updated 2 weeks ago
- A curated list of resources related to privacy engineering☆156Updated 9 months ago
- PipelineDP is a Python framework for applying differentially private aggregations to large datasets using batch processing systems such a…☆277Updated 2 weeks ago
- Code samples and documentation for SmartNoise differential privacy tools☆133Updated 3 years ago
- A Unified Framework for Quantifying Privacy Risk in Synthetic Data according to the GDPR☆89Updated 2 weeks ago
- SDNist: Benchmark data and evaluation tools for data synthesizers.☆36Updated last month
- Anonymization methods for network security.☆158Updated 4 months ago
- Python Implementation for Mondrian Multidimensional K-Anonymity (Mondrian).☆174Updated last year
- Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.☆666Updated 2 months ago
- Course Material for the Tutorial on Privacy Enhancing Technologies and PPML☆13Updated 3 years ago
- Privacy-Preserving Machine Learning (PPML) Tutorial☆41Updated last year
- ☆36Updated last year
- The core library of differential privacy algorithms powering the OpenDP Project.☆368Updated this week
- Python language bindings for smartnoise-core.☆76Updated 2 years ago
- ☆10Updated 4 years ago
- UCLANesl - NIST Differential Privacy Challenge (Match 3)☆24Updated 6 years ago
- ☆269Updated last year
- ☆39Updated 2 years ago
- The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy☆525Updated 10 months ago
- A software package for privacy-preserving generation of a synthetic twin to a given sensitive data set.☆53Updated 10 months ago
- Privacy Testing for Deep Learning☆205Updated last year
- Privacy-preserving XGBoost Inference☆49Updated 2 years ago
- PhD/MSc course on Machine Learning Security (Univ. Cagliari)☆210Updated last month
- Practical examples of "Flawed Machine Learning Security" together with ML Security best practice across the end to end stages of the mach…☆112Updated 3 years ago
- ☆43Updated 4 years ago
- ☆26Updated last year
- An implementation of the tools described in the paper entitled "Graphical-model based estimation and inference for differential privacy"☆103Updated last week
- Federated Learning Utilities and Tools for Experimentation☆190Updated last year
- Official Repo for the 30DaysOfFLCode Challenge Initiative☆74Updated 6 months ago