An Automated System for Assessing Threat and Risk of Corporate Espionage

Award Information
Agency:
Department of Defense
Branch
Defense Advanced Research Projects Agency
Amount:
$374,978.00
Award Year:
2003
Program:
SBIR
Phase:
Phase II
Contract:
DAAH0103CR165
Award Id:
58371
Agency Tracking Number:
02SB1-0157
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
1000 Thomas Jefferson Street N.W., Washington, DC, 20007
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
095609165
Principal Investigator:
Gary Jackson
President and CEO
(202) 298-2660
gjackson@psynapsetech.com
Business Contact:
Stephanie Jackson
Vice President of Adminis
(202) 298-2661
sjackson@psynapsetech.com
Research Institution:
n/a
Abstract
The ABC Behavioral model, pattern classification methodology, and an expert, rule based system are proposed as key approaches to develop a commercially based assessment instrument that is capable of determining the likelihood that external or internalcorporate espionage could be directed against the organization being assessed. To develop the predictive instrument, the ABC Model and pattern classification component will identify key predictors of corporate espionage gleaned from historical data. Thesehistorically based patterns will be augmented by subject matter experts who will provide additional knowledge concerning context, trends not seen in historical data, details of corporate espionage not included in historical cases, and details andrecommendation to be included in automated, interpretive reporting of results. The application developed will be validated both with historical information and by a panel of corporate espionage experts. The application will be web-based. Using well-tested,reliable, and validated modeling methodologies developed for DARPA, the corporate espionage assessment instrument proposal expands this past work to the specific area of asymmetric corporate espionage threat and applied threat assessment.

* information listed above is at the time of submission.

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