Automated Identification and Semi-automated Resolution of Conflicting, Suspicious, Inconsistent and Deceptive Information

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8750-13-C-0174
Agency Tracking Number: F131-051-2385
Amount: $136,686.00
Phase: Phase I
Program: SBIR
Awards Year: 2013
Solicitation Year: 2013
Solicitation Topic Code: AF131-051
Solicitation Number: 2013.1
Small Business Information
32 Regents Park, East Amherst, NY, -
DUNS: 133375571
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Geoff Gross
 Research Scientist
 (585) 967-2712
Business Contact
 Rakesh Nagi
Title: President and CEO
Phone: (716) 510-1055
Research Institution
ABSTRACT: This proposal details a software suite which will be developed for the automated identification and semi-automated resolution of conflicting, suspicious, inconsistent and deceptive information (CSI-Info). The methods employed will adapt previous research work performed by the PI"s while advancing the work to better meet the needs of the challenging CSI-Info identification and resolution domain. The multi-stage software suite will include processing elements to: (1) Recognizing and resolve formatting inconsistencies (specifically data field formats); (2) Perform common referencing and uncertainty alignment (unit conversion and qualitative/quantitative observation transformation and comparison); (3) Perform anomaly detection for statistical and rule-based anomalies; (4) Identify data association transitivity requirement violations (to make sure that if X is similar to Y and Z, then Y and Z should also be similar for consistency sake); (5) Extend stochastic graph matching technique to identify exclusive OR (XOR) violations; (6) Develop human touch points for the resolution of CSI-Info (for the cases where resolution was not automatically attained). These research and implementation tasks will be performed over a period of 9 months with intermediate system testing and evaluation summarized in a deliverable format. BENEFIT: The research study and software prototype will provide an analyst with a range of CSI-Info identification and resolution mechanisms. The application of these methods can improve entity resolution, data association, common referencing, and ultimately fusion and situation understanding activities. These in turn can lead to thwarting insurgencies, uncovering terror cells, preventing IED attacks and result in stable and peaceful nation states. In commercial applications these technologies can help avert financial crime, credit card fraud, and result in fewer loan defaults, for example. The improved decision-making resulting from CSI-Info detection and resolution can save many lives and save millions in financial wealth.

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

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