Novel Detection Mechanisms for Advanced Persistent Threat

Award Information
Agency:
Department of Defense
Branch
n/a
Amount:
$149,040.00
Award Year:
2013
Program:
SBIR
Phase:
Phase I
Contract:
W911QX-13-C-0108
Award Id:
n/a
Agency Tracking Number:
O123-IA4-2166
Solicitation Year:
2012
Solicitation Topic Code:
OSD12-IA4
Solicitation Number:
2012.3
Small Business Information
2051 Lama Mountain, Box 289, Questa, NM, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
150907996
Principal Investigator:
Rick Dove
CEO/CTO
(575) 586-1536
dove@parshift.com
Business Contact:
Rick Dove
CEO/CTO
(575) 586-1536
dove@parshift.com
Research Institution:
n/a
Abstract
This project employs a massively parallel, low cost, low power, associative-memory pattern detection processor soon-to-market by a major semiconductor producer. Phase 1 will use a microprocessor emulator to develop, test, and analyze"very large scale anomaly detectors"(developed under a prior SBIR project) organized in a 3-level hierarchical sense-making architecture of spatial, temporal, and correlative pattern detectors for employment at network endpoints. A fourth level in the sense-making hierarchy will be deferred until Phase 2, and provide cross-endpoint network-wide correlative pattern detection. The Phase 1 project has three principle objectives: 1) to establish performance and values of the very large scale anomaly detectors for detecting zero-day and advanced persistent threat attacks, and 2) to develop a semi-supervised learning process that converges on a sparse but sufficiently optimal pattern dictionary for each of the three levels in the hierarchy. and 3) to demonstrate capability to discover previously unseen attacks with high true positives and low false positives.

* information listed above is at the time of submission.

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