July 30, 2013
Speaker: Prof. Matthias Grossglauser (Associate Professor, School of Computer and Communication Sciences, EPFL)
The proliferation of online social networks, and the concomitant accumulation of user data, give rise to hotly debated issues of privacy, security, and control. One specific challenge is the sharing or public release of anonymized information without accidentally leaking personally identifiable information (PII). Unfortunately, it is often difficult to ascertain that sophisticated statistical techniques, potentially employing additional external data sources, could not break anonymity.
We consider an instance of this problem, where the object of interest is the structure of a social network, i.e., a graph describing users and their links. One may naively assume that anonymizing the users' identities would preclude an attacker from obtaining any PII from such a graph. However, recent work on network de-anonymization has demonstrated that this is not necessarily the case: the availability of node and link data from another domain, which is correlated with the anonymized network, has been used to re-identify the anonymized nodes. In this talk, we discuss statistical models based on random graphs for the de-anonymization problem, and derive conditions for network privacy, and insights about vulnerabilities. This has important implications for policies for sharing of anonymized network information.
Matthias Grossglauser is an Associate Professor in the School of Computer and Communication Sciences at EPFL. He received his Diplôme d'Ingénieur en Systèmes de Communication degree from EPFL in 1994, the M.Sc. degree from the Georgia Institute of Technology in 1994, and the Ph.D. from the University Pierre et Marie Curie (Paris 6) in 1998. His research interests are in social and information networks, graph mining, privacy, mobile and wireless networking, and network traffic measurement and modeling. He received the 1998 Cor Baayen Award from theEuropean Research Consortium for Informatics and Mathematics (ERCIM), the IEEE INFOCOM 2001 Best Paper Award, and the 2006 CoNEXT/SIGCOMM Rising Star Award. He served on the editorial board of IEEE/ACM Transactions on Networking, and on numerous Technical Program Committees.
From 2007-2010, he was with the Nokia Research Center (NRC) in Helsinki, Finland, holding the positions of Laboratory Director, then of Head of a tech-transfer program focused on data mining, analytics, and machine learning. In addition, he served on Nokia's CEO Technology Council, a technology advisory group reporting to the CEO. From 2003-2007, he was an Assistant Professor at EPFL. From 1998 to 2002, he was a Senior, then Principal Member of Research Staff in the Networking and Distributed Systems Laboratory at AT&T Research in New Jersey. From 1995 to 1998, he was a Ph.D. student at INRIA Sophia Antipolis, France.