Privacy-aware urban mobility data harvesting
Συλλογή αστικών δεδομένων κίνησης διασφαλίζοντας την ιδιωτικότητα των αντικειμένων
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Keywords
Privacy ; Data harvesting ; Urban mobilityAbstract
With the growth of smart cities and broadening usage of location-based services with mobile devices, there is rising concern about privacy risks of information that can be inferred from human trajectories. The present thesis entitled "Privacy-aware urban mobility data harvesting" focuses on how sensitive information can be inferred via various privacy attacks; hence, it presents research into potential privacy risks of urban mobility data harvesting. The study first identifies and analyzes common types of privacy attacks that can be executed in real-world scenarios and the types of information that can be accessed and used to identify individuals. This paper subsequently implements, in the Rust programming language, the procedure for evaluation of such risks of privacy attacks. Finally, besides some experiments to assess the suggested implementation's performance in terms of time and accuracy, this thesis shows the comparison of this implementation with the existing state-of-the-art implementation, Scikit-mobility.
Department
Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα ΠληροφορικήςNumber of pages
30Language
EnglishCollections
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Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα