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P22-073 NeuroPlex++

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911NF-22-P-0064
Agency Tracking Number: A22B-T010-0111
Amount: $172,949.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: A22B-T010
Solicitation Number: 22.B
Solicitation Year: 2022
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-09-25
Award End Date (Contract End Date): 2023-03-24
Small Business Information
3600 Green Court Suite 600
Ann Arbor, MI 48105-1111
United States
DUNS: 009485124
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Henry Phillips
 (850) 501-2601
Business Contact
 Christian Thomas
Phone: (407) 437-4334
Research Institution
 The Regents of the University of California
 Kathleen Wrobel
10889 Wilshire Blvd, Suite 920
Los Angeles, CA 90095-7191
United States

 (310) 794-0558
 Nonprofit College or University

To achieve overmatch in C4I versus peer adversaries, Army intelligence analysts need support in detecting and classifying instances of adversary tactics, techniques, and procedures (TTP) execution across domains. Complex Event Processing (CEP) tools need improvement to meet this requirement, in order to detect entity behaviors and movements that may be observed by different sensors, or separated in time by minutes or longer. TTPs also change frequently, and must be recognized when they occur in different operational environments and across domains. An additional challenge is that relatively little training data may exist to help a system learn to detect and recognize instances of TTP execution. The proposed NeuroPlex++ tool builds on previous work and uses a hybrid approach to solve this problem, leveraging deep neural networks for mapping unstructured high dimensional sensor data into symbolic percepts embedded in space and time with associated uncertainty, along with a logical layer to enable the direct incorporation of human domain knowledge to enable CEP and TTP recognition across operational environments and domains, meeting the retraining objective of this topic.

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

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