Any of these resonate with you? Then read on!
Specifically, we argue that:
1. There is no known effective method to anonymize location data, and no evidence that it’s meaningfully achievable.
2. Computing re-identification probabilities based on proof-of-concept demonstrations is silly.
3. Cavoukian and Castro ignore many realistic threats by focusing narrowly on a particular model of re-identification.
4. Cavoukian and Castro concede that de-identification is inadequate for high-dimensional data. But nowadays most interesting datasets are high-dimensional.
5. Penetrate-and-patch is not an option.
6. Computer science knowledge is relevant and highly available.
7. Cavoukian and Castro apply different standards to big data and re-identification techniques.
8. Quantification of re-identification probabilities, which permeates Cavoukian and Castro’s arguments, is a fundamentally meaningless exercise.
https://boingboing.net/2014/07/09/big-data-should-not-be-a-faith.html
