Reverse Engineering of Web Cookies

When is too late for your private data?

Master thesis (2023)

Authors

A.P. Taneva Electrical Engineering, Mathematics and Computer Science

Contributors

G. Smaragdakis Cyber Security - EEMCS (mentor)
S. Picek Cyber Security - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2023 Aleksandra Taneva
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Published Date

08-03-2023

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Nowadays, the online industry contributes to a multi-billion dollar business, facilitates most of the population's everyday activities, and processes vast amounts of data, including personal data. Current work aims to explore the inconsistency or consistency of the content obtained by the websites to generate cookies based on various data that the user provides when visiting a web page, being by explicit consent or not. Some websites integrate with third-party companies that track users and collect their data. For this research, a custom-made Selenium-based web application (crawler) visits the Top 50 Alexa most visited websites and observes the cookies that are collected before the user's consent. After a brief data set analysis, a significant inconsistency in the cookies' count that deviates per location, device type, and operating system is detected. The results show that some websites collect private data, even though users are not informed about the collected data, and the consent for using cookies is not retrieved. These results imply that tracking persists as a serious concern. Tracking raises ethical and legal matters due to its potential adverse effect on users' data. That is why it is essential to analyse the content these trackers obtain, e.g., location, internet protocol address, and browsing history. Subsequently, to suggest possible techniques to avoid tracking.