Analysis of user tracking techniques in web feeds

OData support
Dr. Gulyás Gábor György
Department of Automation and Applied Informatics

The new, information-driven services of Web 2.0 have brought many new opportunities to the world of internet. Due to their conquer, content-sharing has become one of the key moments of the worldwide network. The new features, that are coming to the front, had great business opportinities, and they still have to this day, because users receive huge amounts of information every day.

It brings not only advantages but disadvantages as well. Many companies and services have been created for the only reason to track users and build a profiles from the information obtained about them, and to either use it themselves or sold it to other companies. The privacy of surfing users - thanks to this type of activities - becomes more endangered and more vulnerable to attacks. Since this vulnerability will only intensify in the near future, with the born of new techniques, so the protection of our own data should get more and more attention.

There are many web-based and well-known tracking methods, however, in the first part of this thesis, I will examine these methods in the aspect of various web feeds. First, I am going to demonstrate the traditional and the new web-based tracking techniques too. Then I come to the characterization of test applications, and finally I am going to use the own-built criteria system to analyze tracking and attacking techniques of web feeds.

In the second part of the thesis I am going to estimate the presence of used methods on the feeds of the compiled list that are worth to check. I will find out what kind of tracking techniques are pages using, and to what extent are they doing it. After that, I will aggregate the results, draw inferences from them and recommend options to maximize the protection of privacy.


Please sign in to download the files of this thesis.