Award Abstract #0311686
Collaborative Research: Automated and Adaptive Diversity for Improving Computer Systems Security

NSF Org:	CNS Division of Computer and Network Systems
Initial Amendment Date:	August 6, 2003
Latest Amendment Date:	May 25, 2005
Award Number:	0311686
Award Instrument:	Continuing grant
Program Manager:	Karl N. Levitt CNS Division of Computer and Network Systems CSE Directorate for Computer & Information Science & Engineering
Start Date:	August 15, 2003
Expires:	July 31, 2007 (Estimated)
Awarded Amount to Date:	$250000
Investigator(s):	Stephanie Forrest forrest@cs.unm.edu (Principal Investigator)
Sponsor:	University of New Mexico 1700 Lomas Blvd. NE ALBUQUERQUE, NM 87131 505/277-4186
NSF Program(s):	TRUSTED COMPUTING
Field Application(s):
Program Reference Code(s):	HPCC, 9218, 9150, 7254, 1667
Program Element Code(s):	2802

ABSTRACT

Proposal Number: NSF Collaborative Proposals CCR-0311808 and

CCR-0311686

Title: Automated and Adaptive Diversity for Improving Computer System

Security

PI: Stephanie Forrest

Abstract: Diversity is an important source of robustness in biological systems. Because each individual has slightly different properties, it is unlikely that any single pathogen will eliminate or escape the

entire population. By contrast, today's computer systems are largely homogeneous, being overwhelmingly dominated by one or two operating systems and a few common applications from a handful of software

vendors. This fact is routinely exploited by attackers via Internet worms such as Code Red, which infected over 250,000 systems in just nine hours using a single buffer overflow vulnerability.

The project will develop methods for diversifying computer systems automatically and systematically -- exploring diversity at various levels of a system and for various purposes, e.g., to make a system

more difficult to compromise, to make a system more difficult to damage even after a successful compromise, and to make it more difficult for a successful compromise to evade detection. In order

to succeed, many of the mechanisms explored in this work must hide or disguise information about system specifics from an attacker, and this theme will underlie several of the projects.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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C. Warrender, S. Forrest, and F. Koster.  "Modeling intercellular interactions in early Mycobacterium infection,"  Bulletin of Mathematical Biology,  v.?,  2006,  p. ?.

D. L. Chao, M. P. Davenport, S. Forrest, A. S. Perelson.  "The effects of thymic selection on the range of T cell cross-reactivity,"  European Journal of Immunology,  v.35,  2005,  p. 3452.

G.Barrantes, D. Ackley, S. Forrest, and D. Stefanovic.  "Randomized instruction set randomization,"  ACM Transactions on Information Systems Security (TISSEC),  v.8:1,  2005,  p. 3.

J. Balthrop, S. Forrest, M. Newman, and M. Williamson.  "Technological networks and the spread of computer viruses,"  Science,  v.304,  2004,  p. 527.

M. Glickman, J. Balthrop, and S. Forrest.  "A machine learning evaluation of an artificial immune system,"  Evolutionary Computation Journal,  v.13:2,  2005,  p. 179.

P. Holme, J. Karlin, and S. Forrest.  "Radial structure of the Internet,"  Proc. Royal Academy A,  v.463,  2007,  p. 1231.

S. Forrest and C. Beauchemin.  "Computer Immunology,"  Immunological Reviews,  v.216,  2007,  p. 176.


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