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Blurring – residential and
nonresidential areas
For residential areas, we can control the extent of blurring because
we have good data on population density; blurring to the census
tract level might do the trick, and the census tells us what geographic
distance we have to go to in order to blur that much.
Blurring will be less precise in nonresidential areas if we don’t
know the densities there. For example, when someone is in a non-retail
commercial sector, we may not know whether that one building has
enough people to provide anonymity, or whether we need to blur to
the block, or larger unit.
What is needed is a map containing data on the density of people
in each area at representative times throughout the day. Happily,
it is relatively easy to collect this density data without significant
privacy risk. How? The privacy risk comes primarily from tracks
which show someone going from X, to Y, and, then, to Z. But, to
get the density data, we don't need to link someone's being in X,
with that person's subsequent travel to Y and Z. So, we can collect
density data without too much risk by using a “snapshot”
method, rather than a tracking method; we'd simply record device
locations every sample interval without including in the dataset
a unique identifier which would otherwise make it possible to tell
which phone was which (and where each phone was previously).
Once the density data is obtained, it can be used to blur (in real
time) locations in nonpublic, nonresidential areas.
Back to "Misc. Details on the Method"
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