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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-07042019-094734


Tipo di tesi
Tesi di laurea magistrale
Autore
NARETTO, FRANCESCA
URN
etd-07042019-094734
Titolo
A Framework for privacy risk prediction of sequence data.
Dipartimento
INFORMATICA
Corso di studi
INFORMATICA
Relatori
relatore Prof.ssa Monreale, Anna
Parole chiave
  • data privacy
  • prediction of privacy risk
  • privacy risk assessment
Data inizio appello
26/07/2019
Consultabilità
Non consultabile
Data di rilascio
26/07/2089
Riassunto
Nowadays there is a great interest in developing techniques assessing the user privacy risk due to the requirements of the GDPR.
Traditional frameworks conduct an evaluation of the privacy risk by simulating a series of possible privacy attacks.
The main drawback is their efficiency. We propose a user-centric privacy risk assessment framework that employs machine learning models for predicting the users’ privacy risk. Our interest is on time series data. Our framework also involves a privacy risk explanations component. Its main task is to provide an explanation to the end-user, describing the reasons why his data put him at risk. The proposed approach solves the problem of efficiency for the privacy assessment methodology and gives the opportunity to assign the privacy risk to a user without looking at the data of other users.
Experimental results highlight good predictive performances and are promising in terms of explainability for increasing the user awareness.
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