NIST seeks proposals for approach to de-identifying data sets

The National Institute of Standards and Technology (NIST) recently announced its Unlinkable Data Challenge, which seeks proposals for approaches to de-identifying personal information in large databases to improve individuals’ privacy.

The program aims to help the public safety community conduct research using data from personal digital devices and large databases without compromising privacy. The data supports research in fields such as thwarting crime, fighting fires and fighting the spread of epidemics, but it often contains identifying information.

“The key to unleashing the data’s power for the public safety community lies in finding automated ways to effectively ‘de-identify’ personal information while maintaining the data’s analytic value,” NIST said in a press release. “The goal of the challenge is to create these methods, which will help the public safety community make better decisions while protecting the public from data leaks and cyberattacks.”

The challenge consists of three phases. The first phase seeks proposals of overall conceptual approaches to de-identifying a data set. The next two phases will involve developing and refining algorithms to implement the approaches. $190,000 of total prize money will be split among the three phases.

Submissions for the first phase close on July 26.