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Cloud-based Autonomous Real-time Malware Analysis (CARMA)

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911NF-11-C-0240
Agency Tracking Number: A11A-020-0114
Amount: $99,869.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: A11a-T020
Solicitation Number: 2011.A
Timeline
Solicitation Year: 2011
Award Year: 2011
Award Start Date (Proposal Award Date): 2011-09-12
Award End Date (Contract End Date): N/A
Small Business Information
625 Mount Auburn Street, Cambridge, MA, -
DUNS: 115243701
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Terry Patten
 Principal Scientist
 (617) 491-3474
 tpatten@cra.com
Business Contact
 Mark Felix
Title: Contracts Manager
Phone: (617) 491-3474
Email: mfelix@cra.com
Research Institution
 University Louisiana at Lafayette
 Ruth Landry
 Office of Research and Sponsor
PO Box 43610
Lafayette, LA, 70504-
 (337) 482-1922
 Nonprofit college or university
Abstract
The amount of new malware encountered daily is accelerating at an unprecedented rate, an explosion that is also reflected in target and attack vector diversity. There has also been a dramatic increase in the use of malware kits, a problem in its own right because kits allow adversaries to easily create one-time-use malware variants for which generic signatures and general solutions are neither practical nor effective. We propose to demonstrate a heterogeneous cloud-based defense system that detects novel malware and provides critical functionality in the areas of real-time analysis, scalability, accuracy, and systemic coverage and knowledge distribution. Under our Cloud-Based Autonomous Real-Time Malware Analysis (CARMA) effort, we will study how to use cloud resources to perform deep malware analyses that will address two critical questions. To address the"Is it a variant of existing malware?"question, we will use ideas from genetics and evolutionary biology to perform evolutionary analysis of malware to determine the inheritance relationships among parts of malware across samples. To address the"What does it do?"question, we will use ideas from functional linguistics to identify and characterize the functions of the malware and its constituent parts.

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

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