Fingerprinting isn’t always possible to defeat, and its not always possible to avoid making accounts (work and school accounts)
However, it should be possible to fill up tracked data with meaningless garbage and reduce the signal-to-noise ratio. Ex: a bot that browses random products on amazon to reduce profiling accuracy.
Do you guys know of any tools that do this? Anything from browser extensions to command line scripts, to anonymous group-accounts.
Just FYI You would have to be using the same exact browser configuration you normally browse with, otherwise the fingerprint it uses will be different.
Yeah, cookies, account logins, and other stuff make it hard too. Ex: randomly exploring gmail emails at different times of day, but not actually marking emails as read.
Right, even the most secure/private browser cannot help opsec failures… if only one person visits the same website(s) at the same time every day, you are not anonymous. But we all must define our own threat models and apply what’s realistic for us individually.
Except for shared unique similarities. Fingerprinting designers know “not all data is good data” and will then filter out bad data and use hard to change charateristics, like hardware or software similarities, which can enable cross-browser fingerprinting.
What is a “shared unique similarity”? Sounds a lot like something that isn’t unique to me…
Unique to you, shared between your different browsers.