Understanding, Using and Protecting Online Social Networks

Tuesday, November 3, 2009 - 4:48pm

When: MONDAY, November 9, 2009 from 3:30pm – 4:30pm
Where: Computer Science Conference Room, Harold Frank Hall Rm. 1132

Computer Science, UCSB


The lack of accountability in the Internet architecture has made
possible a number of attacks and malicious behavior, including spam,
denial-of-service attacks, and online fraud. Despite continuous efforts
to combat these threats, they remain an intrinsic part of the Internet

The recent rise of online social networks (OSNs) offers a promising new
approach to addressing the lack of identity and accountability in the
Internet. By approximating offline relationships online, OSNs provide a
way to inject credibility and reliability into otherwise insecure
network applications. Researchers have recently proposed an emerging
class of Internet applications that leverage social relationships to
improve security and performance.

Critical questions remain in the study and development of these
applications. Can these applications actually be effective in real life?
And if so, how can we predict their effectiveness when they are deployed
on real social networks?

In this talk, we will describe recent research that tries to answer
these questions using measurement-based studies of online social
networks and applications. Using measurements of a socially-enhanced
web auction site, we show how social networks can actually reduce fraud
in online transactions. We then discuss the evaluation of social network
applications, and argue that existing methods using social graphs can
produce to misleading results. We use results from a large-scale study
of the Facebook network to show that social graphs are insufficient
models of user activity, and propose the use of “interaction graphs” as
a more accurate model. We construct interaction graphs from our
Facebook datasets, and use both types of graphs to validate two
well-known social-based applications (Reliable Email and SybilGuard).
Our results reveal new insights into both systems and confirm our
hypothesis that choosing the right graph model significantly impacts
predictions of application performance.

Finally, we briefly outline new projects focused on protecting user
privacy in online social networks.


Ben Zhao is an assistant professor in the Computer Science department at
UCSB, where his research interests include large-scale distributed
systems, data intensive computing, security and privacy in networked
systems, and wireless and vehicular networks. He is a recipient of the
NSF CAREER Award, MIT Tech Review TR-35 Award, and ComputerWorld
Magazine’s Top IT Innovator under 40 Award.

HOST: Divy Agrawal