Passive Deanonymization of Tor Hidden Services [pdf]

tl;dr "we don't think they can uniquely identify public websites that well though they can obviously identify someone is using hidden services, so we should probably make it more difficult to identify hidden services"

I may trust my mother a lot, and maybe she wouldn't rat me out to the cops, but that doesn't mean she can stand up to enhanced interrogation techniques. Tor alone will not protect you completely, but it's better than nothing.

Listen to the advice of thr Tor developers themselves.

They say Tor should be but one tool in your overall privacy/anonymity/security toolbox.

Relying on Tor alone is probably a bad idea.

Visitor count fluctuations differ on sites with differing content. HN for example has far fewer visitors during the weekend.

I don't think shared hosting is very common with tor hidden services, especially sharing the same hidden service address. There are probably examples of it, but they're rare.

A likely use of hidden-service-deanonymisation is finding the server that runs a drug market (silk road-style). Those are overwhelmingly likely to be on their own server.

Another commenter already linked to the tor project's response, which suggests that this kind of website profiling attack is less accurate in the real world than their introduction would suggest.

In general, it depends. Statistical correlation analysis works pretty well as long as you have enough data, the data points you're looking at aren't specifically designed to change constantly (such as with a strong boolean function in a stream cipher correlation attack), and they don't introduce false positives. But if the data points you're looking at are strong indicators of unique data and your training method can correlate strongly with a specific user's requests, it shouldn't be too difficult.

Section 7 (page 12) goes over website fingerprinting and how they're able to gain a significant positive match and low false-positive match rate. They can more easily identify noise from signal than previously thought, we're only looking at hidden services (which number far fewer than the number of public websites), hidden service pages change much less frequently than public ones, and they exclude data points that could raise the false positive rate.

Also note that the classifiers here were even better at identifying specific clients than what hidden services they were accessing. So, not only is your hidden service not safe, neither are your users :-)