Engaging Future Generation War Fighters and Civilians in Research to understand Cyber and Electronic Warfare, Cyber Defense, and Data Driven Modeling Tools
Abstract
In view of our diminishing technological advantage over our enemies, Naval Research and Development Framework and Addendum (https://www.onr.navy.mil/our-research/navalresearch- framework) identifies that We must be responsive to the accelerating pace of technology development and create pathways that will result in the timely fielding of new naval capabilities. This Framework document emphasizes that in order to maintain our naval forces superiority over our enemies in spite of increasing volume, speed and complexity of threats, we need to invest in basic research and proceed along a fully synchronized RDT&E continuum with agility to pursue new breakthroughs at the rapid pace of discovery and technology development. It is stresses that to maintain our superiority over enemies, our Navy must fieldnew technology-based warfighting capabilities. The Naval R&D Framework and Addendum (NRDFA) identifies Emerging Power of Data and Expanding Technical Foundation as two of the four fundamental trends that drive the competition and present opportunities for competitive advantage.In view of the above, we present in this proposal, an umbrella research program where we will engage and train undergraduate ROTC cadets and US nationals in hands-on research activities in three framework priority areas as identified in the NRDFA: (a) Augmented Warfighting, (b) Sensing and Sense-Making, and (c) Scalable Lethality. We build these research projects around three thematic areas: Computational propaganda (CP), Validation of threats of infectiondiseases (VT), and Machine learning based predictive modeling (ML).Research projects in the CP category involve training the students on the detection of computational propaganda, and effective cyber-deception to defend against emergent electronic warfare threats. The VP category of research aims at engaging the participating undergraduate researchers to develop new mathematical and phylogenetic models for epidemiology to best protect our military personnel serving abroad against the threats of pathogenic viruses, bacteria, and parasites that they would not normally experience in domestic service. Projects in ML category involves application of machine learning methodologies to improve the flow prediction accuracies of existing computational fluid dynamics modeling approaches, and use principles ofDeep Learning in turbulent flow structure identification. Lessons learned from these two aspects of the CP projects can be used in more accurately predicting possible trajectories of airborne particles, such as radiological, chemical, or biological materials in gaseous, liquid, or solid forms. Each of the three thematic areas will include 1-2 projects, with 2-4 students working in each project. The projects are deigned in consultation with Major Blake Smith, who overseas UNCCharlotte Army ROTC activities; Major Smith is the Chair of UNC Charlotte Military Science Department. Though our primary focus will be attracting ROTC cadets to these projects, the projects will be open to all US citizens pursuing a STEM undergraduate degree at an accredited US university. For the non-ROTC participants, preferences will be given to the veterans and members of military connected families. Graduate Research Assistants (GRA) will mentor theparticipants in the program under the guidance of faculty supervisors.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 31, 2020
- Source ID
- N000142012804
Entities
People
- Mesbah Uddin
Organizations
- Office of Naval Research
- United States Navy
- University of North Carolina at Charlotte