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Protocol Feature Identification and Removal

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-19-C-0633
Agency Tracking Number: N18A-018-0123
Amount: $999,995.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: N18A-T018
Solicitation Number: 18.A
Timeline
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-08-12
Award End Date (Contract End Date): 2021-08-19
Small Business Information
11245 West Bernardo Court, Suite 102, San Diego, CA, 92029
DUNS: 178927500
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: N
Principal Investigator
 Peter Robinson Peter Robinson
 President
 (619) 243-0961
 probinson@pjrcorp.com
Business Contact
 Peter Robinson
Phone: (619) 243-0961
Email: probinson@pjrcorp.com
Research Institution
 University of Florida
 Stephanie Gray Stephanie Gray
 702 Radio Road
Gainesville, FL, 32611
 (352) 392-1582
 Nonprofit college or university
Abstract
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 II STTR Proposal, in partnership with the University of Florida (UF), seeks to automatically customize or subset the protocols to allow only necessary functionality. PJR and UF intend to reverse the trend toward onesize-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 work is to research, validate, test, and demonstrate approaches to resolving challenges to automatically identify and remove targeted features from common protocols. UF will research the application 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 automate the process of safely remove or disable features within protocols.

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

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