kjam / practical-data-privacy
Practical Data Privacy
☆86Updated 5 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
- Privacy-Preserving Machine Learning (PPML) Tutorial☆37Updated 8 months ago
- A toolkit for tools and techniques related to the privacy and compliance of AI models.☆99Updated 7 months ago
- SDNist: Benchmark data and evaluation tools for data synthesizers.☆34Updated last week
- Code samples and documentation for SmartNoise differential privacy tools☆132Updated 2 years ago
- Course Material for the Tutorial on Privacy Enhancing Technologies and PPML☆12Updated 3 years ago
- A Unified Framework for Quantifying Privacy Risk in Synthetic Data according to the GDPR☆76Updated 7 months ago
- Privacy Testing for Deep Learning☆197Updated last year
- UCLANesl - NIST Differential Privacy Challenge (Match 3)☆23Updated 5 years ago
- ☆44Updated 2 years ago
- ☆39Updated 2 years ago
- ☆35Updated last year
- Official Repo for the 30DaysOfFLCode Challenge Initiative☆69Updated 2 months ago
- Tools and service for differentially private processing of tabular and relational data☆262Updated last month
- PhD/MSc course on Machine Learning Security (Univ. Cagliari)☆208Updated 2 months ago
- PipelineDP is a Python framework for applying differentially private aggregations to large datasets using batch processing systems such a…☆274Updated 3 weeks ago
- Privacy Preserving Machine Learning (Manning Early Access Program)☆32Updated 2 years ago
- Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.☆626Updated last month
- ☆43Updated 3 years ago
- ☆10Updated 3 years ago
- Python language bindings for smartnoise-core.☆75Updated last year
- ☆24Updated last year
- A library for running membership inference attacks against ML models☆142Updated 2 years ago
- Differentially Private Synthetic Data Generation [DP-SDG] - Experimental Setups & Knowledge Base - WORK IN PROGRESS☆11Updated 2 years ago
- ☆264Updated 10 months ago
- Privacy-preserving XGBoost Inference☆48Updated last year
- An implementation of the tools described in the paper entitled "Graphical-model based estimation and inference for differential privacy"☆98Updated last week
- ☆23Updated last year
- A software package for privacy-preserving generation of a synthetic twin to a given sensitive data set.☆51Updated 5 months ago
- A Platform for Secure Analytics and Machine Learning☆300Updated last year
- Evaluating variety of k-Anonymity techniques.☆54Updated last year