Last year, Microsoft began the development of a differential privacy platform in collaboration with Harvard University"s Institute for Quantitative Social Science. Utilizing the OpenDP Initiative, the tech giant"s goal was to create an open solution that keeps individual data private, while simultaneously providing researchers with insights based on huge amounts of data.
Today, Microsoft has announced that the platform has been launched, with its resources made available on GitHub for all interested parties to test, build, and support.
A royalty-free license under Microsoft"s own differential privacy patents will be granted to the world, allowing people using the platform to make their own datasets securely available to others. Julie Brill, CVP, Deputy General Counsel, and Chief Privacy Officer at Microsoft, commented on the development of this platform in the following manner:
"We need privacy enhancing technologies to earn and maintain trust as we use data. Creating an open source platform for differential privacy, with contributions from developers and researchers from organizations around the world, will be essential in maturing this important technology and enabling its widespread use."
For those who are unaware of how the system of differential privacy works, it essentially involves the adding of statistical noise to datasets in order to mask and protect the privacy of individuals, while keeping the useful information that needs to be extracted still accurate. At a point where querying data may lead to personal privacy being in a state where it is close to being compromised, additional querying for the data is halted.
The open-source nature of the developed platform means that the implementation cannot only be validated, but researchers can also collaborate to help improve the technology in use. Microsoft believes that the insights which are achieved as a result will lead to "an enormous and lasting impact", and will help in the development of solutions to a variety of problems.