4 ms·
It's been a couple years since I read the literature so I might be wrong, but iirc differential privacy fuzzes the number of matches instead of the data points
by losteric 9y ago
It's been a couple years since I read the literature so I might be wrong, but iirc differential privacy fuzzes the number of matches instead of the data points themselves.
That is, in your example differential privacy would precisely display the start and end points but the number of riders would be fuzzed (perhaps showing 4 departures and 2 arrivals at the respective location/time).
Also, iirc, offline differential privacy can outright remove data points while online system can block sufficiently deanonymizing queries.
One of the criticisms of differential privacy is that it can render the data useless... I definitely found that held true for my data. In the end, my company simply decided against releasing (or collecting) any customer data.
- yoz-y 9y agoDoesn't it also introduce noise into the dataset? It could modify rides at random, let's say that 10% of rides would have the start or end point swapped with some other ride or completely changed. That way the information in aggregate is still useful, but no one measurement is necessarily true and also you can not use the lack of a data point as a proof of anything.
- losteric 9y ago> That way the information in aggregate is still useful, but no one measurement is necessarily true and also you can not use the lack of a data point as a proof of anything. This is great, succinct, description of the goals of differential privacy. > Doesn't it also introduce noise into the dataset? It could modify rides at random, let's say that 10% of rides would have the start or end point swapped with some other ride or completely changed. It can. There are variants, and offline/online systems operate differently.