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SATPAM - Self Awareness Through Predictive Abstraction Modeling

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-13-P-1022
Agency Tracking Number: O123-IA2-4066
Amount: $149,997.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: OSD12-IA2
Solicitation Number: 2012.3
Solicitation Year: 2012
Award Year: 2013
Award Start Date (Proposal Award Date): 2013-02-22
Award End Date (Contract End Date): 2013-08-21
Small Business Information
6011 West Courtyard Drive Bldg 5, Suite 300
Austin, TX -
United States
DUNS: 158034665
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: Yes
Principal Investigator
 Jonathan Mugan
 Principal Investigator
 (512) 682-4730
Business Contact
 Todd Spears
Title: VP, R&D Solutions
Phone: (512) 682-4747
Research Institution

Current computer systems are dumb automatons; their blind execution of instructions makes them open to attack. Their inability to reason means they don"t consider the larger, constantly changing context outside their immediate inputs. Their nearsightedness is particularly dangerous because, in our complex systems, it is difficult to prevent all exploitable situations. Additionally, the lack of autonomous oversight of our systems means they are unable to fight through attacks. Keeping our adversaries completely out of our systems may be an unreasonable expectation, and our systems need to adapt to attacks and other disruptions to achieve our objectives. What is needed is an autonomous controller within the computer system that can sense the state of the system and reason about that state. 21CT proposes SATPAM, which uses prediction to learn abstractions that allow it to recognize the right events at the right level of detail. These abstractions allow SATPAM to break the world into small, relatively independent, pieces that allow employment of existing reasoning methods.

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

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