|
|
|
|
|
by vehemenz
1956 days ago
|
|
Unfortunately, I think these studies are a bit naive because the proprietary, data-driven, probabilistic fingerprinting models used by Facebook and LinkedIn (to name two of the most elaborate fingerprinters) are years ahead of anything a few researchers could come up with. 1. Get a gazillion users on your site 2. Require a user account tied to a real person 3. Log IP, host, geolocation, and as many JavaScript/browser APIs as you can (there are hundreds at this point) 4. Among the fields you track, find the ones that ones that are the most stable and unique over time 5. Assign some probabilities to these fields to eliminate false positives 6. Generate personas for users for when they are at home, work, one their phone, etc. |
|
That's fingerprinting, traditionally. Hence, the "Cookieless tracking" header right there on the page. If you are tying in other data, that's data aggregation for your business case and is fundamentally unrelated.
I mean, generating personas and whatever "false positives" mean, has nothing to do with fingerprinting. If you cant differentiate from an anon user to another, that's data too.