Google LLC is stepping up its efforts to support user privacy and security with the open-source release today of a new “multiparty computation” tool called Private Join and Compute.

It’s designed to help organizations compare confidential data sets. The way the tool works is that it allows two parties to analyze and compare shared data sets without actually revealing the contents of that information to the other party.

Google said this could be useful in a number of scenarios. For example, if someone wants to see how a private, encrypted data set containing ad click-to-sales conversion rates correlates with a similar data set from another party, they can do so without disclosing the actual numbers to the other person.

In a blog post co-authored by Google engineers Amanda Walker, Sarvar Patel and Moti Yung, Google explained that Private Computing Private Join and Compute is based on a cryptographic protocol called Private Set-Intersection. This protocol was originally created for a Chrome browser extension called Password Checkup, which lets users test login credentials against a data set of compromised logins and passwords without revealing what those credentials are.

But Private Join and Compute goes a bit further: It masks the data that represents the intersection of the two data sets, revealing only the results of the calculations based on the data.

“We continually invest in new research to advance innovations that preserve individual privacy while enabling valuable insights from data,” Google’s researchers wrote. “Many important research, business, and social questions can be answered by combining data sets from independent parties, where each party holds their own information about a set of shared identifiers, some of which are common.”

The only thing from the data sets that’s revealed are aggregated statistics that reveal commonalities within the information that’s compared.

Google said the tool could be useful in several industries where privacy is a paramount concern, including healthcare. “By sharing the technology more widely, we hope this expands the use cases for secure computing,” the researchers said. “This is just the beginning of what’s possible.”

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