Professor Matthias Grossglauser
EPFL Switzerland
School of Computer and Communication Sciences IC
Computer Science Building, Room 150
Faculty Host: Donald Towsley
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 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.
Bio:
Matthias Grossglauser is an associate professor in the School of
Computer and Communication Sciences at EPFL. He is interested in
social and information networks, privacy, mobile and wireless
networking, and network traffic engineering. He received his Diplome
d'Ingenieur en Systemes de Communication 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 VI) in 1998.
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. From 1998 to 2002, he was Member of Research Staff at AT&T
Research in New Jersey.
He received the 1998 Cor Baayen Award, 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.