Publication Date
2022
Conference Title
Modeling, Simulation and Visualization Student Capstone Conference 2022
Conference Track
Infrastructure Security/Military Application
Document Type
Paper
Abstract
The Data-Enabled Advanced Training Program for Cybersecurity Research and Education (DeapSECURE) was introduced in 2018 as 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. By its third year, DeapSECURE, like many other educational endeavors, experienced abrupt changes brought by the COVID-19 pandemic. The training had to be retooled to adapt to fully online delivery. Hands-on activities were reformatted to accommodate self-paced learning. In this paper, we describe and assess the third and fourth years of the project and compare them with the first half of the project, which implemented in-person instruction. We also indicate major improvements and present future opportunities for this training program to advance the cybersecurity field.
Keywords:
Big data, Machine learning, Neural networks, High performance computing training, Cybersecurity
Start Date
4-14-2022
End Date
4-14-2022
Recommended Citation
Dodge, Bahador; Strother, Jacob; Asiamah, Rosby; Arcaute, Karina; Purwanto, Wirawan; Sosonkina, Masha; and Wu, Hongyi, "DeapSECURE Computational Training for Cybersecurity: Third-Year Improvements and Impacts" (2022). Modeling, Simulation and Visualization Student Capstone Conference. 1. DOI: 10.25776/7691-p669 https://digitalcommons.odu.edu/msvcapstone/2022/infrastructuremilitary/1
DOI
10.25776/7691-p669
Included in
Data Storage Systems Commons, Engineering Education Commons, Information Security Commons
DeapSECURE Computational Training for Cybersecurity: Third-Year Improvements and Impacts
The Data-Enabled Advanced Training Program for Cybersecurity Research and Education (DeapSECURE) was introduced in 2018 as 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. By its third year, DeapSECURE, like many other educational endeavors, experienced abrupt changes brought by the COVID-19 pandemic. The training had to be retooled to adapt to fully online delivery. Hands-on activities were reformatted to accommodate self-paced learning. In this paper, we describe and assess the third and fourth years of the project and compare them with the first half of the project, which implemented in-person instruction. We also indicate major improvements and present future opportunities for this training program to advance the cybersecurity field.