Web user identification with fuzzy fingerprints

Fingerprint identification is a well-known technique in forensic sciences. The basic idea of identifying a subject based on a set of features left by the subject actions or behavior can be applied to other domains. Identifying a web user based on a user fingerprint is one such application. This paper considers the problem of extracting fingerprints from web usage logs and matching them with those obtained from a set of known users. It presents an innovative fuzzy fingerprint algorithm based on vector valued fuzzy sets. Used sites are used as base features to create the fingerprint. The assumption is that sites accessed by each user remain approximately stable and are distinctive. The paper presents the proposed algorithm and shows some experimental results that validate the approach. The use of fast and compact algorithms is critical due to the possible huge number of users, and allows this method to be used on near real time.