Please use this identifier to cite or link to this item: http://hdl.handle.net/10609/151546
Title: Data Utility Evaluation Framework for Graph Anonymization
Author: Casas-Roma, Jordi  
Citation: Casas-Roma, J. [Jordi]. (2020). Data utility and privacy evaluation framework for graph anonymization. Actas XV Reunión Española sobre Criptología y Seguridad de la Información (RECSI). p. 123-128
Abstract: Anonymization of graph-based data is a problem which has been widely studied over the last years and several anonymization methods have been developed. Information loss measures have been carried out to evaluate the noise introduced in the anonymized data. However, there is no consensus about how to evaluate perturbation and data utility in privacypreserving and anonymization scenarios, where released datasets contain some noise to hinder re-identification processes. Thus, it is quite complex to compare different methods or algorithms in literature. In this paper we propose a framework to evaluate and compare anonymous datasets in a common way, providing an objective score to clearly compare methods and algorithms.
Keywords: privacy-preserving
anonymity
evaluation framework
data utility
social networks
Document type: info:eu-repo/semantics/conferenceObject
Version: info:eu-repo/semantics/publishedVersion
Issue Date: 5-Oct-2018
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