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，减少了攻击者的机会窗口，增加了攻击成本。MTD解决方案涉及范围广泛的高级技术专门知识，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为计算机科学的高级本科生和研究生开发一个MTD课件，重点是基于网络的MTD技术。此外，将建立一个基于云的动手实验室来支持MTD实验室，这将增加学生和教育工作者在有限的计算机网络和系统安全能力的实验室环境中的访问。建议的MTD课程将作为与MTD实验室存储库关联的教科书发布，允许教师构建新的MTD课程或选择部分教材将其合并到当前的课程中。项目小组还将与行业伙伴合作，制定课程内容，并举办教师培训讲习班，传播课程材料。所有创建的课程内容和实验将供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等技术，目前该领域的教育资源应该针对这些领域。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。该项目将侧重于四个相互依存的任务：(a)通过创建支持SDN、NFV和MTD的软件组件来构建MTD教育能力，并建立MTD实验室存储库和api以增强MTD学习成果；(b)开发以学期为基础的长期课程课程和以短期培训为导向的MTD教学内容；(c)制定全面的评估计划，让内部和外部独立评估人员使用开发的课程内容和实验室；以及(d)与业界伙伴合作，举办教师培训工作坊，尽量传播已开发的多媒体发展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.