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Unified Logging Architecture for Performance and Cybersecurity Monitoring

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-19-C-0538
Agency Tracking Number: N19A-012-0177
Amount: $139,881.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N19A-T012
Solicitation Number: 19.A
Solicitation Year: 2019
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-06-21
Award End Date (Contract End Date): 2019-12-18
Small Business Information
4401 Wilson Boulevard Suite 810
Arlington, VA 22203
United States
DUNS: 606926769
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Shawn Kline Shawn Kline
 Sr. System Engineer I
 (703) 522-5563
Business Contact
 Teddy Kidd
Phone: (703) 522-4032
Research Institution
 Carnegie Mellon University - Software Engineering Institute
 Matthew Milazzo Matthew Milazzo
4500 Fifth Avenue
Pittsburgh, PA 15213
United States

 (412) 268-2527
 Federally Funded R&D Center (FFRDC)

In order to achieve real-time monitoring, analysis, and alerting for complex systems, a unified logging architecture must exist that can support the collection and analysis of big data. Our technical objective is to develop a unified logging architecture that supports collection, aggregation, storage, and analysis of system performance and cybersecurity logs, events, and alerts produced by Naval Control Systems (NCS). IDT is a Department of Defense industry leader in automated test and analysis for real-time defense systems. Carnegie Mellon University – Software Engineering Institute (SEI) is the industry subject matter expert on cybersecurity and data distribution. IDT and SEI are teaming together to provide the Navy the desired capability. IDT and SEI will define and create a prototype Kafka-Based Unified Logging Architecture framework (K-BULA). K-BULA provides real-time, dynamic pipelines for active and passive data to be stored and analyzed, resulting in full cyber situational awareness for mission critical systems. Our solution is capable of extracting data from networks transparently; it will also extract data from nodes by leveraging a lightweight agent installed on the node itself; it will be deployed on a dedicated server that has interfaces into the nodes and network enclaves that are present in a typical NCS.

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

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