Nin / Herranz Privacy and Anonymity in Information Management Systems

New Techniques for New Practical Problems
1. Auflage 2010
ISBN: 978-1-84996-238-4
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 198 Seiten, eBook

Reihe: Advanced Information and Knowledge Processing

As depicted in David Lodge’s celebrated novel Small World, the perceived size of our world experienced a progressive decrease as jet airplanes became affordable to ever greater shares of the earth’s population. Yet, the really dramatic shrinking had to wait until the mid-1990s, when Internet became widespread and the information age stopped being an empty buzzword. But small is not necessarily beautiful. We now live in a global village and, alas, some (often very powerful) voices state that we ought not expect any more privacy in it. Should this be true, we would have created our own nightmare: a global village combining the worst of conventional villages, where a lot of information on an individual is known by the other villagers, and conventional big cities, where the invidual feels lost in a grim and potentially dangerous place. Whereas security is essential for organizations to survive, individuals and so- times even companies also need some privacy to develop comfortably and lead a free life. This is the reason why individual privacy is mentioned in the Univ- sal Declaration of Human Rights (1948) and data privacy is protected by law in most Western countries. Indeed, without privacy, the rest of fundamental rights, like freedom of speech and democracy, are impaired. The outstanding challenge is to create technology that implements those legal guarantees in a way compatible with functionality and security. This book edited by Dr. Javier Herranz and Dr.

Zielgruppe

Research

Autoren/Hrsg.

Nin, Jordi

Herranz, Javier

Inhaltsverzeichnis

Overview.- to Privacy and Anonymity in Information Management Systems.- Advanced Privacy-Preserving Data Management and Analysis.- Theory of SDC.- Practical Applications in Statistical Disclosure Control Using R.- Disclosure Risk Assessment for Sample Microdata Through Probabilistic Modeling.- Exploiting Auxiliary Information in the Estimation of Per-Record Risk of Disclosure.- Statistical Disclosure Control in Tabular Data.- Preserving Privacy in Distributed Applications.- From Collaborative to Privacy-Preserving Sequential Pattern Mining.- Pseudonymized Data Sharing.- Privacy-Aware Access Control in Social Networks: Issues and Solutions.

Über Autor(innen)

Jordi Nin (Barcelona, Catalonia, 1979; BSc 2004, MSc 2007, PhD 2008 all in Computer Science) is a post-doctoral researcher at the Artificial Intelligence Research Institute (IIIA-CSIC) near Barcelona, Catalonia, Spain. His fields of interest are privacy technologies, machine learning and soft computing tools. He has been involved in several research projects funded by the Catalan and Spanish governments and the European Community. His research has been published in specialized journals and major conferences (around 30 papers). Javier Herranz obtained his PhD in Applied Mathematics in 2005, in the Technial University of Catalonia (UPC, Barcelona, Spain). After that he spent 9 months in the Ecole Polytechnique (France) and 9 months in the Centrum voor Wiskunde en Informatica (CWI, The Netherlands), as a post-doctoral researcher, granted with an ERCIM fellowship. From January 2007, he works as a post-doctoral researcher at IIIA-CSIC (Bellaterra, Spain). His research interests include the design and analysis of cryptographic protols and the study of privacy preserving operations involving databases.