DeapSECURE 网络安全计算培训:社区广泛采用的进展情况

Wirawan Purwanto, Bahador Dodge, K. Arcaute, M. Sosonkina, Hongyi Wu
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引用次数: 0

摘要

网络安全研究和教育数据化高级计算培训计划(DeapSECURE)是一项非学位培训,由六个模块组成,涵盖了广泛的网络基础设施技术,包括高性能计算、大数据、机器学习和高级密码学,旨在缩小当前网络安全课程与高级研究和工业项目所需要求之间的差距。自 2020 年以来,对这些课程模块进行了更新和调整,以适应完全在线的教学方式。实践活动也进行了调整,以适应自定进度的学习。在本文中,我们总结了该项目四年来的情况,比较了现场教学和在线教学的方法,并概述了所吸取的经验教训。模块内容和实践材料将作为开源教育资源发布。我们还指出了未来的发展方向,即扩大 DeapSECURE 培训项目的规模并提高其采用率,从而为各地的网络安全研究带来益处。
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DeapSECURE Computational Training for Cybersecurity: Progress Toward Widespread Community Adoption
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 refor-matted 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.
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