Static Analysis of AI Systems

Award Information
Agency:
Department of Defense
Branch
Defense Advanced Research Projects Agency
Amount:
$99,000.00
Award Year:
2004
Program:
SBIR
Phase:
Phase I
Contract:
W31P4Q-04-C-R141
Award Id:
68725
Agency Tracking Number:
03SB2-0189
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
317 N. Aurora Street, Ithaca, NY, 14850
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
603978321
Principal Investigator:
PaulAnderson
Senior Software Engineer
(607) 273-7340
paul@grammatech.com
Business Contact:
RayTeitelbaum
CEO
(607) 273-7340
tt@grammatech.com
Research Institute:
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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