SaTC: EDU: Learning Moving Target Defense Concepts: Teaching and Training Curricula Development Based on Software Defined Networking and Network Function Virtualization

移动目标防御（MTD）是一种新的安全概念，它增加了攻击者的不确定性和复杂性，减少了他们的机会窗口，并增加了他们的攻击成本。MTD解决方案涉及广泛的先进技术专业知识，这是当前教育模式所缺乏的。来自亚利桑那州立大学的项目建议开发一个面向计算机科学高年级本科生和研究生的MTD课件，重点是基于网络的MTD技术。此外，还将建立一个基于云的实践实验室来支持MTD实验室，这将增加学生和教育工作者在计算机网络和系统安全能力有限的实验室环境中的访问。拟议的MTD课程将作为与MTD实验室存储库相关联的教科书出版，允许教师构建新的MTD课程或选择部分教材将其纳入当前课程。项目团队还将与行业合作伙伴合作开发课程内容，并提供教师培训研讨会以传播课程材料。所有创建的课程内容和实验室都将由教师和学生免费下载。MTD解决方案涉及机器学习，人工智能和大数据分析模型的技术，该领域的现有教育资源应该解决这些领域。拟议的项目将解决如何构建一个急需的实践学习模块的研究挑战，该模块可以轻松地部署在现有的云服务平台上，以学习和实验新的计算机网络和安全技术，如软件定义网络（SDN），网络功能虚拟化（NFV）和MTD。该项目将重点关注四个相互依存的任务：（a）通过创建支持SDN、NFV和MTD的软件组件，以及建立MTD实验室资源库和API来增强MTD学习成果，从而构建MTD教育能力;（B）开发长期学期课程和短期培训导向的MTD教学内容;（c）通过让内部和外部独立评价人员参与，实施一项全面评价计划，以使用已制定的课程内容和实验室;及（d）与业界伙伴合作，举办教师培训工作坊，以最大限度地传播已发展的MTD学习内容和实践练习。

Moving Target Defense (MTD) is a new security concept to increase uncertainty and complexity for attackers, reduce their window of opportunity and increase the costs of their attack efforts. MTD solutions involve a wide-range of advanced technical expertise, which current education models lack. The project from Arizona State University proposes to develop an MTD courseware for both senior undergraduate level and graduate level in computer science focusing on network-based MTD technologies. Additionally, a cloud-based hands-on laboratory will be established to support MTD labs, which will increase access to students and educators in lab environments with limited computer networking and system security capabilities. The proposed MTD curricula will be published as a textbook associating with a MTD lab repository allowing instructors to build a new MTD course or pick part of the teaching materials to incorporate them into their current curricula. The project team will also work with industry partners to develop the course content and provide a Teacher Training workshop to disseminate the course materials. All the created course content and labs will be freely downloadable by instructors and students.MTD solutions involve technologies in machine learning, artificial intelligence, and big data analysis models, and current education resources in this realm should address these fields. The proposed project will address the research challenge on how to build-out a much-needed hands-on learning module that can be easily deployed on existing cloud service platforms to learn and experiment with new computer networking and security technologies such as Software Defined Networking (SDN), Network Function Virtualization (NFV), and MTD. This project will focus on four interdependent tasks: (a) building the MTD education capability by creating software components to support SDN, NFV, and MTD, and establishing MTD lab repository and APIs to enhance MTD learning outcomes; (b) developing both long-term semester-based course curriculum, and short-term training oriented MTD teaching contents; (c) conducting a comprehensive evaluation plan by involving both internal and external independent evaluators to use the developed course content and labs; and (d) working with industry partners and hosting a Teacher Training workshop to maximally disseminate developed MTD learning contents and hands-on exercises.