MAAG Maria

Doctor
Equipo : MLIA
Fecha de salida : 30/09/2015
https://lip6.fr/Maria.Maag

Dirección de investigación : Patrick GALLINARI

Co-supervisión : DENOYER Ludovic

Automatic Learning of Anonymization Functions for Graphs and Dynamic Graphs

Data privacy is a major problem that has to be considered before releasing datasets to the public or even to a partner company that would compute statistics or make a deep analysis of these data. Privacy is insured by performing data anonymization as required by legislation. In this context, many different anonymization techniques have been proposed in the literature. These techniques are difficult to use in a general context where attacks can be of different types, and where measures are not known to the anonymizer. Generic methods able to adapt to different situations become desirable.
We are addressing the problem of privacy related to graph data which needs, for different reasons, to be publicly made available. This corresponds to the anonymized graph data publishing problem. We are placing from the perspective of an anonymizer not having access to the methods used to analyze data. A generic methodology is proposed based on machine learning to obtain directly an anonymization function from a set of training data so as to optimize a tradeoff between privacy risk and utility loss. The method thus allows one to get a good anonymization procedure for any kind of attacks, and any characteristic in a given set. The methodology is instantiated for simple graphs and complex timestamped graphs. A tool has been developed implementing the method and has been experimented with success on real anonymized datasets coming from Twitter, Enron or Amazon. Results are compared with baseline and it is showed that the proposed method is generic and can automatically adapt itself to different anonymization contexts.

Defensa : 08/04/2015

miembros del jurado :

Fabrice Rossi, Professeur, Université Panthéon-Sorbonne (Rapporteur )
Benjamin Nguyen, Professeur, INSA Val de Loire (Rapporteur)
Patrick Gallinari, Professeur, Université Pierre et Marie Curie
Ludovic Denoyer, Professeur, Université Pierre et Marie Curie
Bernd Amann, Professeur, Université Pierre et Marie Curie
Maryline Laurent, Professeur, Télécom SudParis
Philippe Jacquet, Directeur de recherche, Alcatel-Lucent Bell Labs
Hakim Hacid, Professeur associé, Zayed University, Emirats Arabes Unis

Fecha de salida : 30/09/2015

Publicaciones 2014-2015

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