Document Type

Article

Publication Date

2024

DOI

10.22369/issn.2153-4136/15/1/1

Publication Title

Journal of Computational Science Education

Volume

15

Issue

1

Pages

2-9

Abstract

The Data-Enabled Advanced Computational Training Program for Cybersecurity Research and Education (DeapSECURE) is a non-degree training consisting of six modules covering a broad range of cyberinfrastructure techniques, including high performance computing, big data, machine learning and advanced cryptography, aimed at reducing the gap between current cybersecurity curricula and requirements needed for advanced research and industrial projects. Since 2020, these lesson modules have been updated and retooled to suit fully-online delivery. Hands-on activities were reformatted to accommodate self-paced learning. In this paper, we summarize the four years of the project comparing in-person and on-line only instruction methods as well as outlining lessons learned. The module content and hands-on materials are being released as open-source educational resources. We also indicate our future direction to scale up and increase adoption of the DeapSECURE training program to benefit cybersecurity research everywhere.

Comments

Originally published in the Journal of Computational Science Education.

Rights

© 2024 Shodor. All rights reserved.

Included with the kind written permission of the editor.

Original Publication Citation

Purwanto, W., Dodge, B., Arcaute, K., Sosonkina, M., & Wu, H. (2024). DeapSECURE computational training for cybersecurity: Progress toward widespread community adoption. Journal of Computational Science Education, 15(1), 2-9. https://doi.org/10.22369/issn.2153-4136/15/1/1

ORCID

0000-0002-2124-4552 (Purwanto)

Download

Share

COinS