Building Cybersecurity Analytics Capacity in Big Data Era: Developing Hands-on Labs for Integrating Data Science into Cybersecurity Curriculum

鉴于大数据的广泛使用，越来越需要培养一支了解大数据背景下网络安全的网络劳动力。北德克萨斯大学的这个项目的目标是将数据科学整合到网络安全课程中，并培养下一代安全专家。该项目建议通过提高网络安全分析师的数量和质量，对日益增长的国家对具有数据分析能力的训练有素的网络安全专业人员的需求产生直接和长期的影响。这个项目的目的是开发适合各种学生学习方式的教学材料。这些材料的设计将使具有不同网络安全知识水平的广泛机构（例如，社区学院到研究密集型机构）的教育工作者能够轻松地将其纳入教学中。拟议的项目旨在开发一套教学模块和实践实验室，利用最先进的数据分析来解决不同的网络安全挑战。这些教学模块将遵循主动学习原则，旨在吸引学生，无论学习方式如何，并确保学生记住所学内容。这些模块将基于现实世界的安全系统，并将被设计为系统地涵盖基本的安全原则。这种方法将允许学生通过现实世界的例子接触数据分析技术及其在网络安全挑战中的应用。该项目旨在制作吸引人的材料，可以很容易地被其他教育工作者采用。为了简化集成并鼓励采用，实践实验室将仅基于开放源代码软件和工具构建，这些软件和工具可免费用于教育目的。此外，它们将通过已经包含所有库和运行实验室所需软件的虚拟机映像进行分发。这种开发方法将允许各种各样的讲师自信地将最先进的数据分析实验室整合到课程中。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Given the wide-spread use of big data, there is a growing need to develop a cyber-workforce that understands cybersecurity in the context of big data. The goal of this project from the University of North Texas is to integrate data science into cybersecurity curriculum and train the next generation of security experts. The project proposes to have direct and long-term impacts on the growing national need for highly-trained cybersecurity professionals with data analytics capabilities, by increasing the number and quality of cybersecurity analysts. This project aims to develop instructional materials that cater to a wide-range of student learning styles. The materials will be designed so that educators at a wide-range of institutions (e.g., community college to research-intensive institutions), and with varying levels of cybersecurity knowledge, can easily incorporate them into their instruction.The proposed project seeks to develop a set of instructional modules and hands-on labs that make use of state-of-the-art data analytics for addressing different cybersecurity challenges. These instructional modules will follow active learning principles designed to engage students, regardless of learning style, and ensure that students retain the content learned. The modules will be based on real-world security systems and will be designed to systematically cover fundamental security principles. This approach will allow students to get exposure to data analytics techniques and their application to cybersecurity challenges via real-world examples. The project aims to produce engaging materials that could be easily adopted by other educators. To simplify integration and encourage adoption, the hands-on labs will be built based on only open source software and tools that are free to use for educational purposes. Further, they will be distributed via virtual machine images that already contain all libraries and required software to run the labs. This approach for development will allow a variety of instructors to confidently integrate state-of-the-art data analytics labs into curriculum with minimal effort.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.