RaffaelBild

arx

ARX is a comprehensive open source data anonymization tool aiming to provide scalability and usability. It supports various anonymization techniques, methods for analyzing data quality and re-identification risks and it supports well-known privacy models, such as k-anonymity, l-diversity, t-closeness and differential privacy.

feasibility-deploy

feasibility-monitoring

suda2

Java implementation of the SUDA2 algorithm for detecting Minimal Sample Uniques (MSUs)

arx

ARX is a comprehensive open source data anonymization tool that has been designed from the ground up to provide high scalability and ease of use. It supports risk-based anonymization, methods for analyzing data utility and re-identification risks, as well as syntactic privacy criteria, such as k-anonymity, l-diversity, t-closeness or δ-presence

blaze

A FHIR® server with internal, fast CQL Evaluation Engine

gta-benchmark

Benchmark

subframe

Java benchmarking library

suda2

Java implementation of the SUDA2 algorithm for detecting Minimal Sample Uniques (MSUs)

RaffaelBild/arx

ARX is a comprehensive open source data anonymization tool that has been designed from the ground up to provide high scalability and ease of use. It supports risk-based anonymization, methods for analyzing data utility and re-identification risks, as well as syntactic privacy criteria, such as k-anonymity, l-diversity, t-closeness or δ-presence

RaffaelBild/blaze

A FHIR® server with internal, fast CQL Evaluation Engine

RaffaelBild/gta-benchmark

Benchmark

RaffaelBild/subframe

Java benchmarking library

RaffaelBild/suda2

Java implementation of the SUDA2 algorithm for detecting Minimal Sample Uniques (MSUs)