"New Tool Simplifies Data Sharing, Preserves Privacy"

A new study by researchers at Carnegie Mellon and IBM introduces a new tool to help maintain the privacy of data shared among companies, organizations, and government. The team of researchers developed a new tool called DoppelGANger that synthesizes new data, mimicking the original dataset while omitting sensitive information. DoppelGANger uses Generalized Adversarial Networks (GANs), which apply machine learning methods to perform this synthesis while keeping the same statistics of the original training data. This article continues to discuss how DoppleGANger simplifies data sharing and maintains the privacy of sensitive data shared between different companies.

Carnegie Mellon University reports "New Tool Simplifies Data Sharing, Preserves Privacy"