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C-SMILE (Cloud-based SOCOM Scalable Man-Machine Identity Learning Environment)

Award Information
Agency: Department of Defense
Branch: Special Operations Command
Contract: H92222-18-C-0001
Agency Tracking Number: S2-0360
Amount: $999,829.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: SOCOM16-003
Solicitation Number: 2016.1
Timeline
Solicitation Year: 2016
Award Year: 2018
Award Start Date (Proposal Award Date): 2017-10-31
Award End Date (Contract End Date): 2019-10-30
Small Business Information
1400 Crystal Drive
Arlington, VA 22202
United States
DUNS: 036593457
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Dr. Jim Nolan
 (703) 414-5002
 jim.nolan@dac.us
Business Contact
 Dana Ho
Phone: (703) 414-5016
Email: dana.ho@dac.us
Research Institution
N/A
Abstract

The balance between the advantages and liabilities of sharing personal and organizational digital information continues to be tested. While modern information technologies have provided tremendous boosts to personal, corporate and public-sector capability growth, they also expose a vulnerability that can cripple organizations and put personal livelihoods at great risk. For U.S. Government personnel, the risks are even greater, particularly for special operators at USSOCOM and other agencies. Without a reliable way to rapidly identify, assess the severity of, and respond to potential leaks, the safety of special operations forces is at risk. In the Cloud-based SOCOM Scalable Man-Machine Identity Learning Environment (C-SMILE) project, DECISIVE ANALYTICS Corporation (DAC) provides a next generation identity management system to manage these risks. The prototype developed in Phase I enables early detection of data leaks posted online and produces a quantified assessment of leak severity to help analysts understand and mitigate personal identity exposure damage that has already occurred. The Phase II system builds upon that work by transforming it from a reactive system to a proactive system that also explores social media data and other open source data to help analysts discover, understand and mitigate potential risks before they can cause damage.

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

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