Original title: DNS User Fingerprint
Authors: SAYED, Karim
Document type: Master’s theses
Year: 2025
Language: eng
Abstract: In today's digital world, maintaining ones privacy has become a more difficult task. This paper explores whether advanced machine learning models can be utilized to fingerprint users can identify users based solely on data collected from a DNS server and to evalu- ate the aspects of a users behavior that can be used to identify them, compromising their privacy. By focusing on behavioral patterns and using feature engineering techniques along side time-series modeling of the users data, this work examines the privacy risks that can arise with DNS-based identification. This work will employ methods like mutual information, variance inflation factor (VIF), and Pearson correlation to select key features, testing them across models both sequential and non-sequential in an attempt to to identify the users. This research makes use of a publicly available dataset detailed in the paper "A user DNS fingerprint dataset", ensuring that the work can be compared with future studies and serve as a foundation for further research. Through time-series modeling and feature dimensionality reduction, an LSTM model was produced that is able to make predictions at 94% accuracy using only a subset of the pro- vided features. Additionally, non-temporal models were used to identify users at 79% accuracy and provide insights to what features impact the predictions the most.
Keywords: DNS; time-series; User Fingerprinting
Citation: SAYED, Karim. DNS User Fingerprint. České Budějovice, 2025. diplomová práce (Mgr.). JIHOČESKÁ UNIVERZITA V ČESKÝCH BUDĚJOVICÍCH. Přírodovědecká fakulta

Institution: University of South Bohemia in České Budějovice (web)
Document availability information: Fulltext is available in the Digital Repository of University of South Bohemia.
Original record: http://www.jcu.cz/vskp/77627

Permalink: http://www.nusl.cz/ntk/nusl-671164


The record appears in these collections:
Universities and colleges > Public universities > University of South Bohemia in České Budějovice
Academic theses (ETDs) > Master’s theses