Modeling security for complex systems

by Alvaro Cardenas

University of California, Berkeley

Date

Monday, March 30, 2009

Time

2:00 p.m. (special time) — 3:00 p.m.

Place

Informatics East (I2), Room 130

Abstract:  In this talk I will present new statistical models for different fields in computer security.  The first half of the talk will focus on network anomaly detection. I will show how statistical methods and game theory can help practitioners understand and design better anomaly detection schemes in the face of intelligent and adaptive attackers. In the second half of the talk I will present some of my ongoing work in two different fields: the cybercrime ecosystem and the security of cyber-physical systems.  In particular, I will show how to use statistical techniques to extract information and model parts of the computer underground market. I will also show how a mathematical model of the physical world can be used to detect computer attacks against cyber-physical systems, and to design attack-resilient control algorithms.

Biography:  Alvaro Cardenas is a postdoctoral scholar at the University of California, Berkeley, where he is a member of the Team for Research in Ubiquitous Secure Technology (TRUST)—an NSF science and technology center. He received his MS and Ph.D. degrees from the University of Maryland, College Park.  While his research interests and work in computer security are very general, he has focused on applications of probability, game theory and machine learning for information security.

Colloquium Provided By:

the School of Informatics