EAGER: SaTC-EDU: A Framework for Developing Attributable Cybersecurity Case Studies

尽管人们越来越意识到网络安全的重要性，但目前网络安全劳动力不足以满足公共、私营和学术部门的需求。该项目将通过增加以标准化和兼容格式提供的有效网络安全学习材料的数量，直接解决对网络安全专业人员日益增长的需求。这些学习材料可以被广泛采用，并用于培训未来的网络安全工作人员。拟议的框架还将激励更多的网络安全学者将他们的研究或教学材料转化为案例研究。这些案例研究将具有归因性，这将扩大社会和社区影响，并通过引用对学者的研究声誉产生积极影响，从而促进他们的学术进步。在这个项目中，团队建议开发一个简单而灵活的框架，名为SAGA (Security Arxiv-Github-kAggle)，学者可以轻松地创建与人工智能（AI）和机器学习（ML）相关的网络安全案例研究。例如，这些案例研究可以说明使用机器学习来检测社交媒体中的恶意活动或使用分类来检测垃圾邮件/网络钓鱼邮件。此外，通过采用学术界的“引用”概念并使用三个公共平台（arXiv, Github, Kaggle）实施，SAGA框架可以轻松地找到已开发的案例研究并在网络安全社区中共享，并允许案例研究的作者适当地认可他们的努力。这种归因旨在鼓励学者参与创建和分享此类网络安全案例研究。最后，该项目提出评估开发的网络安全案例研究在促进学生学习网络安全概念和技能方面的有效性。该项目由安全与可信网络空间（SaTC）计划的一项特别倡议支持，旨在促进网络安全、人工智能和教育领域之间前所未有的合作。SaTC项目与《联邦网络安全研究与发展战略计划》和《国家隐私研究战略》保持一致，旨在保护和维护网络系统日益增长的社会和经济效益，同时确保安全和隐私。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。

Despite increasing awareness of the critical nature of cybersecurity, the cybersecurity workforce is currently insufficient to meet needs across the public, private, and academic sectors. The project will directly address the growing demand for cybersecurity professionals by increasing the number of effective cybersecurity learning materials available in a standardized and compatible format. These learning materials can then be widely adopted and used in training future members of the cybersecurity workforce. The proposed framework will also incentivize additional cybersecurity scholars to turn their research or teaching materials into case studies. These case studies will be attributable, which will expand societal and community impacts and also positively impact scholars’ research reputations via citations and thus enhance their academic progression.In this project, the team proposes to develop a simple yet flexible framework named SAGA (Security Arxiv-Github-kAggle), where scholars can easily create cybersecurity case studies related to artificial intelligence (AI) and machine learning (ML). For example, these case studies might illustrate the use of machine learning to detect malicious activities in social media or detecting spam/phishing emails using classification. Furthermore, by adopting the notion of “citation” from the academic world and implementing it using three public platforms (arXiv, Github, Kaggle), the SAGA framework allows the developed case studies to be found easily and shared across the cybersecurity community and allows the authors of case studies to be appropriately recognized for their efforts. This attribution is intended to encourage scholars’ participation in creating and sharing such cybersecurity case studies. Finally, the project proposes to evaluate the effectiveness of the developed cybersecurity case studies in improving students’ learning of cybersecurity concepts and skills.This project is supported by a special initiative of the Secure and Trustworthy Cyberspace (SaTC) program to foster new, previously unexplored, collaborations between the fields of cybersecurity, artificial intelligence, and education. The SaTC program aligns with the Federal Cybersecurity Research and Development Strategic Plan and the National Privacy Research Strategy to protect and preserve the growing social and economic benefits of cyber systems while ensuring security and privacy.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.