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There is a rapidly growing demand for individuals in cybersecurity and a deficit of persons able to fill those roles. To help meet this need, students not majoring in computing can be utilized to fulfill this demand by exposing them to date mining, cybersecurity practices, and applications of these concepts in the field. This paper presents findings from a twenty-one-week program in which minority undergraduate college students all members of the Reserve Officer Training Coprs (ROTC), were taught computer programming, natural language processing, data visualization, and computer vision fundamentals. Midshipmen and cadets used their newly gained knowledge, teamwork, planning, and communication skills to develop a threat dectection prototype using publicly available social media data. Resuls from pre and post python assessments and post-program interviews that recorded participant attitudes and sefl-efficacy are reported to highlight the programs' effectiveness.
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From Midshipmen to Cyber Pros: Training Minority Naval Reserve Officer Training Corp Students for Cybersecurity
Computing is not only a fundamental part of our daily lives — our national security depends on it. It is essential that members of the Reserve Officer Training Corps (ROTC) be well-versed in computing techniques designed to combat cyber-attacks that continually improve in sophistication and frequency levels. Through computer science education, prospective military leaders are being taught the critical and analytical thinking skills necessary to address these threats. This paper outlines and discusses how underrepresented minority Naval Reserve Officer Training Corps (NROTC) midshipmen, with the majority having little-to-no programming skills or background, were taught the foundational aspects of computer science and exposed to specific cybersecurity concepts in a 15-week program. The program produced many insightful outcomes, one being the development of a tool that collected and analyzed publicly available social media data through the application of data mining algorithms and techniques. Additionally, interviews, which were conducted upon the completion of the program, documented notable findings on the program’s effectiveness and on key concepts for teaching computer science to minority beginners.
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- Award ID(s):
- 1818458
- PAR ID:
- 10178639
- Date Published:
- Journal Name:
- SIGCSE
- Page Range / eLocation ID:
- 726 to 730
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3287324.3287500
