This repository contains my diploma thesis for my undergraduate programme at the Military University of Technology in Warsaw.
The thesis (thesis/document.pdf) is Polish only.
However, I wrote an abstract in English that summarizes the contents of this work.
The Internet has become a somewhat dangerous place for its virtual citizens. Today they must watch out for cyber threats like malware, but also their privacy is at risk all the time. Identification of Internet users became desirable as soon as the Internet became a mass media. Advertising platforms usually exploit identification to track users, and it is often possible to deanonymise them effectively. In this context, fingerprinting is a technique that allows web servers to uniquely identify user devices by examining information retrievable from a device or a browser, where this collection of information is unique for most instances. More vividly: unlike cookies and local storage, browser fingerprint stays the same in incognito/private mode and even when user purges browser data. It is, therefore, a stateless identification. Moreover, studies show that fingerprinting is also challenging to detect.
This work aims to familiarise recipients with the concept of fingerprints, examine privacy/anonymity in their context and describe essential techniques in detail. Apart from the analysis of actively used techniques, the study focuses on the genesis of fingerprints, threats they bring and positive aspects of using another user identification method.
The study also considers the effectiveness of fingerprinting techniques and possibilities of improving it. Since fingerprints tend to change with, for example, changing version of the browser, the proposed fingerprinting enhancement is to create a classifier to cluster similar fingerprints. The paper introduces a heuristic algorithm that uses Levenshtein distance to compute the cumulative difference between two fingerprints' textual components.