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Machine Learning Approaches for Automatic Detection of Web Fingerprinting

Rizzo, Valentino

Machine Learning Approaches for Automatic Detection of Web Fingerprinting.

Rel. Marco Mellia. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2018

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Abstract:

The web is rich of third-party services which use HTML5 and JavaScript snippets, frequently obfuscated, in order to uniquely identify the user and monitor him when surfing the web. This approach, called fingerprinting, constitutes a thread for users' privacy and companies' security. In the thesis it has been conducted a census of the techniques used by tracking services to fingerprint users, the APIs which constitute a source for the unique identification have been identified and it has been developed an automatic, machine learning based detection system for scripts which perform fingerprinting.

Relatori: Marco Mellia
Anno accademico: 2017/18
Tipo di pubblicazione: Elettronica
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering)
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-32 - INGEGNERIA INFORMATICA
Aziende collaboratrici: ERMES CYBER SECURITY S.R.L.
URI: http://webthesis.biblio.polito.it/id/eprint/8227
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