SATPAM - Self Awareness Through Predictive Abstraction Modeling

Award Information
Agency:
Department of Defense
Branch
n/a
Amount:
$149,997.00
Award Year:
2013
Program:
SBIR
Phase:
Phase I
Contract:
N00014-13-P-1022
Award Id:
n/a
Agency Tracking Number:
O123-IA2-4066
Solicitation Year:
2012
Solicitation Topic Code:
OSD12-IA2
Solicitation Number:
2012.3
Small Business Information
6011 West Courtyard Drive, Bldg 5, Suite 300, Austin, TX, -
Hubzone Owned:
N
Minority Owned:
Y
Woman Owned:
Y
Duns:
158034665
Principal Investigator:
JonathanMugan
Principal Investigator
(512) 682-4730
jmugan@21ct.com
Business Contact:
ToddSpears
VP, R&D Solutions
(512) 682-4747
SBIR_Admin@21ct.com
Research Institute:
Stub




Abstract
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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