alt Hacker NewsThen you'd get someone taking the trouble to correlate music and times, to capture someone moving across the city on the map.
Then you'd get profiling to potentially pick out who in particular moved across the city and the exact time of path of their movement.
While this is a nice idea on a local scale, when scaled up it has horrendous privacy implications.
Replies
Then you'd get someone taking the trouble to correlate music and times, to capture someone moving across the city on the map.
Only if someone can move across the city in three minutes.
You would still need a way to map the music to the person listening to it.
Apple and Google could do this if you use their music services, but they already know where you are.
I suppose if I have very unique taste in music and someone else knew about it, they could track me, but this is easily foiled by wearing headphones.
And music fingerprinting is probably incredibly accurate, because it can work similar to linguistic fingerprinting.
There was a site posted to this place a year or so ago, which looked at work frequencies to find alt-accounts.
I don't hide the fact that I use a different account on different computers, so I have a personal account and work accounts and end up changing accounts each time I change jobs.
This site correlated all my accounts, using a very basic fingerprinting technique of looking for words which a user uses uncommonly often.
It found them all with a good degree of confidence.
I haven't seen reference to that site since, I suspect it got taken down.
Musical fingerprinting would be accurate to a similar degree. You wouldn't look for the music someone listens to most, you'd look for uncommon combinations.
A combination a just a few songs that someone listens to unusually more than other people is probably enough for a good enough correlation for fingerprinting.