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Protocol Feature Identification and Removal

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-18-C-0392
Agency Tracking Number: N18A-018-0123
Amount: $124,996.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N18A-T018
Solicitation Number: 18.A
Solicitation Year: 2018
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-06-04
Award End Date (Contract End Date): 2020-02-11
Small Business Information
11245 West Bernardo Court Suite 102
San Diego, CA 92029
United States
DUNS: 178927500
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Peter Robinson Peter Robinson
 (619) 243-0961
Business Contact
 Peter Robinson
Phone: (619) 243-0961
Research Institution
 University of Michigan
 Z. Morley Mao Z. Morley Mao
500 S. State Street
Ann Arbor, MI 48109
United States

 (734) 763-5407
 Nonprofit College or University

Protocols used for communication suffer bloat from a variety of sources, such as support for legacy features or rarely used (and unnecessary) functionality. Traditionally, the Navy subscribes to a blanket adoption of a standard protocol "as is". Unnecessary features are active and can be accessed by both internal and external systems creating security vulnerabilities. PJR Corporation's (PJR's) Phase I STTR Proposal, in partnership with the University of Michigan (UM), seeks to automatically customize or subset the protocols to allow only necessary functionality. PJR and UM intend to reverse the trend toward one-size-fits-all protocols by enabling end users to selectively remove features they do not use or want. Examples of protocol features could include support for legacy functionality or a feature that is made unnecessary by a feature in another layer. The primary objectives of the proposed Phase I work is to research, validate, test, and demonstrate approaches to resolving higher risk technical challenges to automatically identifying and removing targeted features from common protocols. UM will continue it's research of machine learning to protocol feature analysis and discovery, as well as mapping required features to binary/source methods. PJR will research and evaluate approaches to automated code modification/transformation.

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

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