Distributed Anomaly Detection for Wireless Sensor Networks

Dr. Chris Leckie
Department of Computer Science and Software Engineering
University of Melbourne
Abstract:
Identifying misbehaviors is an important challenge for monitoring, fault
diagnosis and intrusion detection in wireless sensor networks. A key
problem is how to minimize the communication overhead and energy
consumption in the network when identifying misbehaviors. We treat this as
a problem of distributed unsupervised learning, where the aim is to build
and combine compact representations of normal behaviour based on the local
measurements from each sensor. These models can be based on
hyperellipsoidal, cluster-based or kernel-based representations. A key
objective is to minimize the communication overhead required to share
these models of normal behaviour between sensor nodes. We demonstrate on
data from real-life sensor networks that our scheme achieves comparable
accuracy compared to equivalent centralized approaches while achieving a
significant reduction in communication overhead.
Bio:
Dr Chris Leckie is an Associate Professor in the Department of Computer
Science and Software Engineering at the University of Melbourne,
Australia. He has made numerous theoretical contributions to the use of
clustering for problems such as anomaly detection in wireless sensor
networks and the Internet. In particular, he has developed efficient
clustering techniques that are specifically designed to cope with highdimensional
and time-varying data streams, which are a major challenge in
network intrusion detection. His work on filtering denial-of-service
attacks on the Internet has been commercialized with an Australian company
(IntelliGuard I.T.), leading to a commercial product. His research has
been published in leading journals and conferences such as ACM Computing
Surveys, IEEE TKDE, Artificial Intelligence, IJCAI and ICML.
Host: Bhaskar Krishnamachari ext. 12528

Location: Frank R. Seaver Science Center (SSC) - 319

Audiences: Everyone Is Invited

Contact: B.Krishnamachari