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% Since 1994, with the introduction of cookies, user tracking and~identification have officially become part of all web browsers~\cite{schwartz_giving_2001}.
% Every human being is similarly identified by~their~fingerprint. 
% The importance of user security has increased with the growing usage of~the~Internet and~technology. 
% Statistics show that as~of~this~year 5.4~billion users had connected to~the~Internet~\cite{internet_world_stats}.

% 95 \% of~the~Internet users work with one of~the~four most widely used web browsers: Chrome, Safari, Microsoft~Edge and~Mozilla~Firefox \cite{browser_usage_data}.
% Web browser developers actively combat this problem by~implementing security mechanisms to~minimise user identification capabilities~\cite{timberg_web_2013}.
% These browsers approach this issue differently, which is~described and~analysed in~this thesis.


In 2024, 5.4 billion people worldwide are connected to the Internet, with 95~\% relying on one of the four most popular web browsers: Google Chrome, Apple Safari, Microsoft Edge, or Mozilla Firefox~\cite{internet_world_stats, browser_usage_data}. 
Like every human has a~unique fingerprint, users leave behind distinctive digital traces as they browse the Web. 
These traces can be used to identify and track individuals in~the~vast digital landscape.

This capability has raised significant concerns about user privacy and security. 
Since the introduction of cookies in 1994, user tracking and identification have become deeply embedded in web technology~~\cite{schwartz_giving_2001}. 
Although web browsers have implemented security mechanisms to address these risks, the~challenge lies in~balancing functionality with privacy~\cite{timberg_web_2013}. 
Each of the major browsers approaches this issue differently, and these approaches are examined and analysed in this thesis.

One of the most common technology used to~track users online is cookies.
The principle of~cookie technology is~to~store a~small file with string data on~an~user's device.
The cookie is then created on~a~server when visiting a~website.
In~general cookies can be divided into two categories: first-party and third-party cookies. 
If~the~visited website places the~cookie, it is the~first-party cookie.
If~another website places the~cookie, it is the~third-party cookie.
Cookies can be used for~customising content or~user tracking.
There are many types of~cookies, their detailed description can be found in~the~chapter~\hyperref[chap:cookies]{2.2}.

Another method used to track users online is browser fingerprinting, a~sophisticated technique used to uniquely identify and track users based on~the~distinctive characteristics of their browsers \cite{eckersley_how_2010}. 
Operating passively in~the~background, it collects data points such as browser type, version, core, installed plugins, screen resolution, battery status, and font rendering. 
These attributes are combined to create a unique fingerprint for each user, allowing continuous tracking across websites without the user’s consent or knowledge.

Unlike cookies, which are created remotely and stored locally on a user’s device, browser fingerprints are generated dynamically each time a web page is visited. 
While cookies can be deleted or modified, fingerprints are much harder to alter or eliminate. 
% This distinction makes fingerprinting a particularly invasive user tracking method, further emphasising the importance of robust privacy protections in web browsers.

To~move on~from~the~third-party cookies, Google has created a~first proposal for~secure personalised advertisements called Federated Learning of~Cohorts, hereafter referred~to~as~FLoC~\cite{google_floc}.
The~concept behind FLoC involved categorising users into~groups or~cohorts according to~their interests.
However, FLoC raised numerous privacy issues and~could serve as~a~user characteristic for~fingerprinting techniques to~track users.

In~light of~these concerns, Google has opted to~discontinue the~development~of FLoC and~introduce a~new technology named Topics API~\cite{google_topics}.
The~primary objective of~Topics, similarly to~FLoC, is to~enable companies to~display pertinent advertisements to~users according to~their interests.
The~distinction between FLoC and~Topics API lies in~the~information provided to~websites: FLoC would send a~cohort~ID representing a~group of~users with~similar interests, whereas Topics delivers a~collection of~the~user's interests, that preserves user's privacy and does not introduce a~new identifier.

The~bachelor thesis aims to~summarise the~possibilities of~modern websites to~form a~user fingerprint and~track users while visiting a~website and~to~compare the~approaches of~modern web browsers to~limiting of user tracking and~forming a~clear user fingerprint. 
A~minor objective for~analysis purposes is~to~implement a~test suite that focuses on~the~most widely used fingerprinting methods. 
The~objective of~the~work is to~discuss the~results of the~analysis and~compare the~security of~the~browsers studied. 