{"repo":"google/differential-privacy","free":true,"listed":false,"github":"https://github.com/google/differential-privacy","clone":"git clone https://github.com/google/differential-privacy.git","description":"Google's differential privacy libraries.","language":"Go","stars":3341,"topics":["privacy","differential-privacy","anonymization"],"license":"Apache-2.0","category":"self-hosted-apps","readme_excerpt":"Differential Privacy NEW: Join our DP community in Slack! This repository contains libraries to generate ε- and (ε, δ)-differentially private (DP) statistics over datasets. It contains the following tools: Privacy on Beam is an end-to-end differential privacy framework for Go built on top of Apache Beam. It is intended to be easy to use, even by non-experts. PipelineDP4j is an end-to-end differential privacy framework for JVM languages (Java, Kotlin, Scala). It supports different data processing frameworks such as Apache Beam and Apache Spark. It is intended to be easy to use, even by non-experts. Three \"DP building block\" libraries, in C++, Go, and Java. These libraries implement basic noise addition primitives and differentially private aggregations. Privacy on Beam and PipelineDP4j use these libraries. A stochastic tester, used to help catch regressions that could make the differential privacy property no longer hold. A differential privacy accounting library, used for tracking privacy budget. A command line interface for running differentially private SQL queries with ZetaSQL. DP Auditorium is a library for auditing differential privacy guarantees. In addition to the tools listed above, it is worth mentioning two related projects developed by OpenMined that make use of our libraries: PipelineDP is an end-to-end differential privacy framework for Python. It is the Python version of PipelineDP4j and is a collaboration between Google and OpenMined. Its source code is located","default_branch":null,"files":null,"tree":[],"storefront":"/r/google","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/google/differential-privacy/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}