Innovative approaches to Situation Modeling, Threat Modeling and Threat Prediction

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$999,998.00
Award Year:
2013
Program:
SBIR
Phase:
Phase II
Contract:
FA8750-13-C-0141
Agency Tracking Number:
F2-6989
Solicitation Year:
2011
Solicitation Topic Code:
OSD11-DR5
Solicitation Number:
2011.
Small Business Information
Data Fusion & Neural Networks, LLC
1643 Hemlock Wy, Broomfield, CO, -
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
130770055
Principal Investigator:
Chris Bowman
President
(303) 469-9828
cbowman@df-nn.com
Business Contact:
Chris Bowman
President
(303) 469-9828
cbowman@df-nn.com
Research Institution:
n/a
Abstract
The technical objective is to improve High-Level Information Fusion (HLIF) robustness by adaptive use of external"data repurposing". The approach provides the functional decomposition and problem-to-solution-space mappings by extending the Dual Node Network (DNN) Data Fusion & Resource Management (DF & RM) Technical Architecture at Level-4 for repurposed data pattern discovery and HLIF context assessment and conformity management (CACM). The DNN integrates across DF & RM levels, permits reuse of designs and software, and prevents one-of-a-kind solutions. The DF & NN team (including world-class fusion experts) has developed affordable methods to discover unknown models without truth data that address bias and uncertainty-in-the-uncertainty issues for'big data'having non-numeric qualitative reports. The semi-supervised methods enable operators to construct repurposed data models mapped into HLIF ontologies based upon a small subset of data. The data-driven methods automatically learn to characterize such repurposed data and learn the correlations with HLIF products which are used to automatically find, characterize, track, and show relevant context for abnormal non-conforming repurposed database behaviors. We will be developing and testing the repurposed data machine learning and CACM prototype on either the real GPS-related Signal-to-Noise-Ratio & space weather for JSpOC Mission System (JMS) or the SYNCOIN data for Distributed Common Ground Station (DCGS) transition.

* information listed above is at the time of submission.

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