I have read a bunch about this, but I am not a data scientist, mathematician, or programmer. I am doing a report on de-identification and this is one of the methods I am researching, but I cannot for the life of me wrap my head around it.
In: Technology
A table has K-anonymity when any row (minus suppression) is part of a set of at least k identical rows. Often this is done by replacing values that can’t helpfully be suppressed, like age or weight, with a range. If you’re doing a study where weight is important, and after you suppress the obvious unique parameters like name you still have less than the k which makes your study’s regulators OK with publishing the data, you might replace weights with ranges; 83 => 80-89. This will make rows that weren’t identical before (like 83 and 86) now identical, increasing k.
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