  In this paper, we demonstrate that it is possible to automatically generate
fingerprints for various web server types using multifactor Bayesian inference
on randomly selected servers on the Internet, without building an a priori
catalog of server features or behaviors. This makes it possible to conclusively
study web server distribution without relying on reported (and variable)
version strings. We gather data by sending a collection of specialized requests
to 110,000 live web servers. Using only the server response codes, we then
train an algorithm to successfully predict server types independently of the
server version string. In the process, we note several distinguishing features
of current web infrastructure.
