Artificially Diverse Operating System (ADOS)

Award Information
Agency:
Department of Defense
Amount:
$79,970.00
Program:
STTR
Contract:
N00014-11-M-0281
Solitcitation Year:
2011
Solicitation Number:
2011.A
Branch:
Navy
Award Year:
2011
Phase:
Phase I
Agency Tracking Number:
N11A-023-0125
Solicitation Topic Code:
N11A-T023
Small Business Information
Charles River Analytics Inc.
625 Mount Auburn Street, Cambridge, MA, -
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
115243701
Principal Investigator
 Curt Wu
 Chief Software Engineer
 (617) 491-3474
 cwu@cra.com
Business Contact
 Mark Felix
Title: Contracts Manager
Phone: (617) 491-3474
Email: mfelix@cra.com
Research Institution
 Boston University
 Melissa Korf
 Office of Sponsored Programs
25 Buick Street
Boston, MA, 02215-
 (617) 353-4365
 Nonprofit college or university
Abstract
Artificial diversity attempts to eliminate the security risks of the IT monoculture. The goal of artificial diversity is to minimize the number of common vulnerabilities across a set of systems by intentionally introducing variations to the structure and process of functionally-equivalent software. Ideally, these variations are invisible to the legitimate user but pose a challenge to the malicious user attempting to find and exploit vulnerabilities. To provide security in computing systems through artificial diversity while maximizing performance, we propose an Artificially Diverse Operating System (ADOS). In this operating system-based approach to diversity, we will apply different diversity techniques within the operating system (OS), so that a network contains a diverse set of systems and individual systems exhibit diversity over time. Because these diversity techniques will be applied within the core OS (i.e., kernel) and are not application-specific, they support any user applications and complement other artificial diversity techniques applied at the application level. To selectively and dynamically apply the diversity techniques, we will design a lightweight reasoning module that optimizes the tradeoff between performance and security.

* information listed above is at the time of submission.

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