yes, but it puts you in the incredibly small bucket of "users that has weird headers that don't mesh well", and makes using the rest of the (many) other fingerprinting techniques all the more accurate.
While it's definitely possible to train a model for that, 'very easy' is nonsense.
Unless you've got some superintelligence hidden somewhere, you'd choose a neural net. To train, you need a large supply of LABELED data. Seems like a challenge to build that dataset; after all, we have no scalable method for classifying as of yet.
yes, but it puts you in the incredibly small bucket of "users that has weird headers that don't mesh well", and makes using the rest of the (many) other fingerprinting techniques all the more accurate.
> If your headers are new every time then it is very difficult to figure out who is who.
https://xkcd.com/1105/
It is very easy unless the IP address is also switching up.
It's very easy to train a model to identify anomalies like that.
While it's definitely possible to train a model for that, 'very easy' is nonsense.
Unless you've got some superintelligence hidden somewhere, you'd choose a neural net. To train, you need a large supply of LABELED data. Seems like a challenge to build that dataset; after all, we have no scalable method for classifying as of yet.