Did you also evaluate fingerprintjs in that context?
Also, did you use css tracking techniques, too? Because there are hundreds of them, especially since the logical conditions spec.
In my own Browser I'm trying to "fake" behaviours, so that it looks like an e.g. Chrome useragent is browsing the website. I'm also filtering a lot of CSS and HTML that could be abused to track users which is, honestly, a lot.
Even the Accept header alone is enough to identify the engine. If you then use a clever webfont you'll have the navigator's version and OS identified due to antialiasing behaving differently...
I'm also curious how you evaluated the fingerprintability...is there a project that you were using for that, which someone could maybe test their own browser against?
Nevermind my last question, I've found your project on github that you used to test the fingerprintability (fp-scanner) [1] and wanted to let others know.
It's stealth [1] and the tl;dr is that I'm trying to build a browser that doesn't compromise on tracking, so it has to have a peer-to-peer cache and some intercepting features, such as rewriting files before the malicious parts reach the client.
It's still very prototypical, so use with care. Lots of things don't work yet.
Did you also evaluate fingerprintjs in that context?
Also, did you use css tracking techniques, too? Because there are hundreds of them, especially since the logical conditions spec.
In my own Browser I'm trying to "fake" behaviours, so that it looks like an e.g. Chrome useragent is browsing the website. I'm also filtering a lot of CSS and HTML that could be abused to track users which is, honestly, a lot.
Even the Accept header alone is enough to identify the engine. If you then use a clever webfont you'll have the navigator's version and OS identified due to antialiasing behaving differently...
I'm also curious how you evaluated the fingerprintability...is there a project that you were using for that, which someone could maybe test their own browser against?