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Cognitive Modeling for Cyber Defense

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-14-P-1068
Agency Tracking Number: N132-132-1105
Amount: $79,999.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N132-132
Solicitation Number: 2013.2
Timeline
Solicitation Year: 2013
Award Year: 2014
Award Start Date (Proposal Award Date): 2013-10-28
Award End Date (Contract End Date): 2014-08-28
Small Business Information
3750 Palladian Village Drive Building 600
Marietta, GA -
United States
DUNS: 179321302
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Laura Strater
 Principal Research Associ
 (770) 790-5420
 laura@satechnologies.com
Business Contact
 Ronda Butler
Title: Sr. Contracts Administrat
Phone: (770) 790-5452
Email: ronda.butler@satechnologies.com
Research Institution
 Stub
Abstract

The Cyber battlespace is extraordinarily dynamic, complex and challenging, with both human and automated adversaries (bots) acting alone and in concert to achieve the desired aims. Before Cyber defenders can act to guard against these attacks, they must first achieve and maintain a level of Situation Awareness (SA) that allows them to identify, understand, and anticipate evolving threats so they can implement strategies to defeat them. Cognitive modeling of Cyberspace SA can assist the Cyber defender in risk monitoring and mitigating activities, supporting an understanding of the effects of attacks on their own Cyber systems, along with the projected evolution of Cyber events and their impacts, and finally executing the proper decisions that are required to disrupt or defeat attacks. The cognitive modeling system proposed will support Cyber defenders in recognizing, characterizing, and responding to threats. CyberFACE uses fuzzy logic based cognitive modeling coupled with a learning-enabled neural network, to produce a cognitive engine built upon the knowledge representation structure of domain experts. Diagnostic outputs comprise recommended actions, targeted to the specific network, as well as the current threat posed by the most likely threat profile identified.

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

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