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NIST’s “Unlinkable Data Challenge” Focuses on Big Data Safety

Contest goal is to make personal data available for scientific research without risking individuals' privacy.

Note: TDWI’s editors carefully choose vendor-issued press releases about new or upgraded products and services. We have edited and/or condensed this release to highlight key features but make no claims as to the accuracy of the vendor's statements.

The National Institute of Standards and Technology (NIST) has announced its Unlinkable Data Challenge to help the public-safety community conduct research using data gathered with personal digital devices and taken from large databases such as driver’s license and health care records. Much of this data includes personal information that can be used to identify its source. Exposing this data risks those individuals’ privacy, but the inability to share it impedes research in many fields, including thwarting crime, fighting fires, and slowing the spread of epidemics.

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 analytics value. 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 has three phases; $190,000 of total prize money will be split among them. The first phase asks competitors to propose an overall conceptual approach to de-identifying a data set. The subsequent two phases will involve developing and refining the algorithms to implement the approach.

Submissions for the first phase close on July 26, 2018. Complete details are available here.

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