Static Analysis of AI Systems

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-04-C-R141
Agency Tracking Number: 03SB2-0189
Amount: $99,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2004
Solicitation Year: 2003
Solicitation Topic Code: SB032-035
Solicitation Number: 2003.2
Small Business Information
317 N. Aurora Street, Ithaca, NY, 14850
DUNS: 603978321
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Paul Anderson
 Senior Software Engineer
 (607) 273-7340
 paul@grammatech.com
Business Contact
 Ray Teitelbaum
Title: CEO
Phone: (607) 273-7340
Email: tt@grammatech.com
Research Institution
N/A
Abstract
Toolkits for Artificial Intelligence (AI) are increasingly being used in government and industry. If such systems have access to sensitive information, it is important to know their security properties. A toolkit may contain low-level flaws, such as buffer-overrun errors that allow an attacker to gain control of the host system. Or, there may be flaws in the rule base of a system implemented with the toolkit that allow unauthorized access to sensitive information. We propose the detailed study of the security properties of CLIPS, a widely used expert-system shell in two parts. The first part will be a detailed analysis of the source code of the system using static analysis tools and other methods to find low-level flaws. The second part will be a study of the CLIPS language and the exploration of static and dynamic approaches to create secure CLIPS programs. A promising approach is to model the CLIPS system as a weighted push down system, and to use model-checking techniques to implement a range of security analyses, including termination analysis and information flow. The results will include a design for a tool to be prototyped in Phase II, and guidelines on how to write a secure CLIPS specification.

* Information listed above is at the time of submission. *

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