Towards a web tracking profiling algorithm

Accurate tracking of web attackers can be used to identify and monitor repeat offenders, and to allow defenders to deter and/or retaliate against the attackers. Tracking of web clients has been difficult since HTTP is a stateless protocol. Existing methods are limited to the current session and are not designed to track a client long-term or through different environments. This paper evaluates and rates the most popular methods of tracking web users in terms of the uniqueness of the information provided by them, and how well they preserve information when a client attempts to remove them. The tracking methods are then combined using a profiling algorithm to correlate all of the available information into a single profile. The algorithm is designed with different weights for each method. Test results demonstrate that this approach accurately determines the correct profile for a client in situations where the individual methods alone could not.