Netcentric Operations Defense Environment (NODE)

Award Information
Agency:
Department of Defense
Branch
Missile Defense Agency
Amount:
$99,999.00
Award Year:
2007
Program:
SBIR
Phase:
Phase I
Contract:
W9113M-07-C-0028
Agency Tracking Number:
B063-001-1080
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
KNOWLEDGE BASED SYSTEMS, INC.
1408 University Drive East, College Station, TX, 77840
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
555403328
Principal Investigator:
Arthur Keen
Senior Research Scientist
(979) 260-5274
akeen@kbsi.com
Business Contact:
Donielle Mayer
Business Operations Manager
(979) 260-5274
dmayer@kbsi.com
Research Institution:
n/a
Abstract
Current approaches to security are flawed because they 1) are highly dependent on characterizing known exploits making them vulnerable to new attack variants, 2) use hub-and-spoke centralized architectures that are not scalable and makes them vulnerable to availability attacks, 3) have single points of failure making them vulnerable to confidentiality, integrity, and availability attacks, 4) focus on perimeter defense, so they are vulnerable to insider threats including compromised hosts, and 5) produce results that overwhelm analysts with low level event data, high false positives, and no guidance on attack variants. Knowledge based Systems, Inc. (KBSI) proposes the Netcentric Operations Defense Environment (NODE). NODE is a new paradigm in computer network defense (CND) that detects network intrusions without 1) signatures cataloged prior to event detection, 2) heuristic rules, and 3) profiles of "normal" system behavior by applying data mining and machine learning technologies originally developed for understanding the function of the human genome. NODE achieves scalability, total coverage, redundancy, and fault tolerance in detecting intrusions by executing distributed data mining and machine learning algorithms over the network hosts (the computing fabric) in order to identify and characterize behavior patterns in the communication among hosts.

* information listed above is at the time of submission.

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