Matrix Algorithm via Subspace Decomposition

Award Information
Agency:
Department of Defense
Branch
Army
Amount:
$100,000.00
Award Year:
2007
Program:
STTR
Phase:
Phase I
Contract:
W31P4Q-07-C-0304
Award Id:
83223
Agency Tracking Number:
A074-002-0293
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
500 West Cummings Park - Ste 3000, Woburn, MA, 01801
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
859244204
Principal Investigator:
TonyFalcone
Group Leader: Image Exploitation
(781) 933-5355
afalcone@ssci.com
Business Contact:
JayMiselis
Corporate Controller
(781) 933-5355
jmiselis@ssci.com
Research Institute:
UNIV. OF ARIZONA
Mark Neifeld
College of Optical Sciences
1630 East University Boulevard
Tucson, AZ, 85721
(520) 621-6102
Nonprofit college or university
Abstract
Our objective is to devise a comprehensive and effective methodology for offering software anti-tamper protection via algorithm obfuscation. A primary Phase I goal will be to apply our techniques in the Kalman Filter setting, and use this as a baseline against which we can compare their effectiveness when applied to other matrix-based algorithms. Necessarily, we will devote appropriate resources to deriving meaningful metrics for measuring their efficacy. Phase I will comprise a proof-of-concept stage. We begin by specifiying a ''recursive or iterative matrix intensive algorithm,'' e.g., a Kalman Fiter. Our ''algorithm level obfuscation technique'' consists of a systematic subspace decompostion applied to pairs of (in general) non-commuting matrices. This approach is similar to an application of the Baker-Campbell-Hausdorff formula when specialized to matrix Lie Groups. In Phase II and III, we will develop the concepts from Phase I into a functional prototype. This will include, but may not be limited to combining (our) matrix-level algorithm obfuscation with tradition software obfuscation techniques. In addition, we will investigate the feasibility of developing ''meta-algorithms'' that can be applied to large classes of matrix-based algorithms, and will thereby not require detailed knowledge of the particular algorithm for which obfuscation is desired.

* information listed above is at the time of submission.

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