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Twiner

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-18-C-0415
Agency Tracking Number: N18A-019-0042
Amount: $124,859.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N18A-T019
Solicitation Number: 18.A
Timeline
Solicitation Year: 2018
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-06-04
Award End Date (Contract End Date): 2019-08-15
Small Business Information
3600 Green Court, Suite 600, Ann Arbor, MI, 48105
DUNS: 009485124
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Dr. Fernando Maymi Dr. Fernando Maymi
 Lead Scientist
 (734) 887-7643
 fernando.maymi@soartech.com
Business Contact
 Laura Schwennesen
Phone: (734) 887-7683
Email: laura.schwennesen@soartech.com
Research Institution
 Georgia Tech Research Institute
 Elizabeth Whitaker Elizabeth Whitaker
 250 14th Street, NW
Atlanta, GA, 30332
 (404) 407-6656
 Nonprofit college or university
Abstract
We currently lack the ability to holistically and autonomously look across all three layers of cyberspace (persona, logical and physical) and identify interesting patterns, which would give us an edge in understanding complex activities in and through cyberspace. To address this challenge, Soar Technology (SoarTech) and the GeorgiaTech Research Institute (GTRI) propose Twiner, an intelligent system that aggregates very large sets of heterogeneous data, correlates them to detect causal relationships and displays both the data and its relationships in a way that enables novel cyberspace operations. Our goal is to allow users to find interesting entities and events and, by selecting them, to see how they are intertwined with others, thereby creating a dynamic, multi-layer map of cyberspace. Twiner will require us to develop novel anomaly detection and large-scale correlation techniques for which our machine learning (ML) expertise is ideally suited. However, since these deductive ML techniques alone are insufficient to establish causation, we will pair them with an abductive reasoning engine. Abductive reasoning starts from a set of observations and finds the likeliest explanation for them using behavioral models. Twiner’s engine will use Soar cognitive agents and a custom model library.

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

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