NIST Develops Privacy-Preserving ‘Encounter Metrics’ That Could Help Slow Down Future Pandemics 

NIST Develops Privacy-Preserving ‘Encounter Metrics’ That Could Help Slow Down Future Pandemics 

NIST researchers developed a cryptographic system using encounter metrics. Encounter ID is a way of labeling an encounter between two people through a random number not linked to the device each person carries. To generate the randomized number Z, each device calculates using their private info (a and b) and what the other device is broadcasting (X and Y). Cryptography ensures that device A's Z is the same as Device B's Z.


Credit: B. Hayes/NIST



When you bump into someone in the workplace or at your local coffee shop, you might call that an “encounter.” That’s the scientific term for it, too. As part of urgent efforts to fight COVID-19, a science is rapidly developing for measuring the number of encounters and the different levels of interaction in a group. 


At the National Institute of Standards and Technology (NIST), researchers are applying that science to a concept they have created called “encounter metrics.” They have developed an encrypted method that can be applied to a device such as your phone to help with the ultimate goal of slowing down or preventing future pandemics. The method is also applicable to the COVID-19 pandemic.  


Their research is explained in a pilot study published in the Journal of Research of NIST


Encounter metrics measure the levels of interactions between members of a population. A level of interaction could be the number of people in a bathroom who are talking to each other or a group of people walking down a hallway. There are numerous levels of interactions because there are so many different ways people can interact with one another in different environments.  


In order to mitigate the spread of an infectious dis ..

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