Automated Tools to Assist FDO Duties

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$99,970.00
Award Year:
2005
Program:
SBIR
Phase:
Phase I
Contract:
FA8750-05-C-0155
Agency Tracking Number:
F051-099-0744
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
SECURBORATION, INC.
695 Sanderling Dr, Indialantic, FL, 32903
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
038379579
Principal Investigator:
Tony Stirtzinger
Principal
(321) 591-3295
tstirtzinger@securboration.com
Business Contact:
Lee Krause
Principal
(321) 591-9836
lkrause@securboration.com
Research Institution:
n/a
Abstract
Foreign Disclosure officers are the personnel in the United States AOC responsible for implementing National Disclosure Policy (NDP) that governs disclosure of United States Classified Military Information (CMI) to foreign governments and international organizations. Increasing emphasis on collaborating with multinational forces has put significant burden on release authorities, especially since the release process requires a manual, review of products. The advent of chat tools have greatly benefited communication among AOC and CAOC personnel but chat communications are impossible for an FDO to manually review. Attempts to solve these types of boundary problems based on keywords have proven to be inadequate. Natural Language Processing techniques can contribute to a solution by extracting linguistic artifacts to get the gist of the input, however, that gist still needs to be evaluated. Even if gist or summaries of chat sessions are captured, it is impractical for the FDO to review all of them. Securboration, teaming with Inxight Corporation and Northrop Grumman Mission Systems Division is pleased to propose an innovative solution entitled Automated Assistance for Foreign Disclosure (A2FD) that addresses these problems by leveraging and extending state of the art natural language processing (NLP) techniques to understand the gist, and using ontology-based inferencing to automate the evaluation of the gist, with only potential violations forwarded to the FDO.

* information listed above is at the time of submission.

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