4 ms·
While this works for some datasets with known statistical properties, it seems unlikely to become a universal option. Differential Privacy relies on the intuiti
by u8mybrownies 6y ago
While this works for some datasets with known statistical properties, it seems unlikely to become a universal option. Differential Privacy relies on the intuition that something is only private of it happens once in a dataset. Multiple times? Must be something humans have in common.
The issue is that you need massive datasets for everything non-personal to start repeating. And one of the parallel constraints of protecting privacy is not centralising massive datasets.
Encrypted computation needed.
- xyzzy_plugh 6y agoIndeed, Differential Privacy is very useful, and it's an incredible step in the right direction for some problems, but it's no silver bullet. Even Homomorphic database encryption is only useful for some use cases. Ultimately there is no escaping understanding the statistical consequences of data.
- v4dok 6y agoEncrypted computation does not protect privacy. You can still compute arbitrary, privacy-violating functions