SBIR-STTR Award

C-SMILE (Cloud-based SOCOM Scalable Man-Machine Identity Learning Environment)
Award last edited on: 9/22/2017

Sponsored Program
SBIR
Awarding Agency
DOD : SOCOM
Total Award Amount
$1,149,829
Award Phase
2
Solicitation Topic Code
SOCOM16-003
Principal Investigator
Jim Nolan

Company Information

Decisive Analytics Corporation (AKA: DAC)

1400 Crystal Drive Suite 1400
Arlington, VA 22202
   (703) 414-5001
   N/A
   www.dac.us
Location: Multiple
Congr. District: 08
County: Arlington

Phase I

Contract Number: D17PC00008
Start Date: 00/00/00    Completed: 00/00/00
Phase I year
2016
Phase I Amount
$150,000
The primary goal of a terrorist-organized data leak is to share private data with the rest of the world. Once acquired, U.S. Government personnel information can provide actionable information to use against the U.S. in the form of direct strike, blackmail, fraud, or impersonation. For special operators at numerous government organizations, this leakage or discovery of personal information can have devastating national and international consequences. 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, we are presenting a next generation identity management system that will provide an integrated suite of scalable, high performance technologies and automated analysis tools. Relying on a strong foundation in probabilistic modeling and natural language processing algorithms, C-SMILE technology enables early detection of data leaks posted online and produces a quantified assessment of leak severity. Our goal in Phase I of this effort is to provide an assessment on the feasibility of applying these technologies and tools to the domain of identity risk management.

Phase II

Contract Number: H92222-18-C-0001
Start Date: 00/00/00    Completed: 00/00/00
Phase II year
2018
Phase II Amount
$999,829
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.