Threat Modeling/Risk Analysis
Lead PI:
Xenofon Koutsoukos
Abstract

With the increased use of cyber physical systems in current defense, medical, and energy applications, it is critical for the infrastructure to remain secure. As such, it is important to identify potential security flaws early in the design process in order to produce a consistent, secure and reliable system with minimal fabrication costs. This task can be accomplished using threat modeling. Threat modeling can be separated into two diverse fragments, asset centric and attack centric threat modeling. Asset centric threat modeling takes the point of view of the defender in order to focus on all of ways that a system can be protected from an attack. Attack centric threat modeling on the other hand focuses on the point of view of the attacker, coming up with all of the possible combinations of actions that can result in the compromise of the system. With the interaction of these two perspectives of threat modeling, the system can be tested against possible attack sequences before fabrication, ensuring a high expectation of system security and reliability after development.

This project focuses on developing an attack centric threat modeling tool using the Generic Modeling Environment (GME). The modeling environment is first developed in a consistent manner to a STRIPS planning problem, and then transformed into a single state machine model using the GReAT tool, allowing for the user modeling interface to be integrated with an external planning library. After integrating the model with the Fast Downward Planning library using the GME DSML C# interpreter api, an action plan can be returned, allowing the modeler to identify the possible methods of compromising the system. Furthermore, this attack centric threat modeling tool will be integrated with an asset centric threat modeling tool currently under development, allowing for a full scale threat modeling testbed.
 

Xenofon Koutsoukos

Xenofon Koutsoukos is a Professor of Computer Science, Computer Engineering, and Electrical Engineering in the Department of Electrical Engineering and Computer Science at Vanderbilt University. He is also a Senior Research Scientist in the Institute for Software Integrated Systems (ISIS).

Before joining Vanderbilt, Dr. Koutsoukos was a Member of Research Staff in the Xerox Palo Alto Research Center (PARC) (2000-2002), working in the Embedded Collaborative Computing Area.
He received his Diploma in Electrical and Computer Engineering from the National Technical University of Athens (NTUA), Greece in 1993. Between 1993 and 1995, he joined the National Center for Space Applications, Hellenic Ministry of National Defense, Athens, Greece as a computer engineer in the areas of image processing and remote sensing. He received the Master of Science in Electrical Engineering in January 1998 and the Master of Science in Applied Mathematics in May 1998 both from the University of Notre Dame. He received his PhD in Electrical Engineering working under Professor Panos J. Antsaklis with the group for Interdisciplinary Studies of Intelligent Systems.

His research work is in the area of cyber-physical systems with emphasis on formal methods, distributed algorithms, diagnosis and fault tolerance, and adaptive resource management. He has published numerous journal and conference papers and he is co-inventor of four US patents. He is the recipient of the NSF Career Award in 2004, the Excellence in Teaching Award in 2009 from the Vanderbilt University School of Engineering, and the 2011 Aeronautics Research Mission Directorate (ARMD) Associate Administrator (AA) Award in Technology and Innovation from NASA.