Collaborative Research: EAGER: SaTC-EDU: Secure and Privacy-Preserving Adaptive Artificial Intelligence Curriculum Development for Cybersecurity

近年来，研究人员已经应用人工智能（AI）来有效地解决网络安全中的重要问题。虽然在人工智能的帮助下，网络安全研究取得了重大进展，但缺乏受过高等教育的工作人员，他们可以解决人工智能和网络安全交叉点的挑战性问题。该项目将通过同时教育来自不同社区的合格个人来培养这样的劳动力。该项目团队将为研究生开发和提供模块化和基于项目的课程，这些课程将涵盖人工智能和网络安全的基础知识。创新课程的开发旨在加强学生体验，并在人工智能和网络安全领域建立一支强大而多样化的劳动力队伍，以填补政府，工业和学术界目前的空白。项目团队将为研究生开发五个模块课程：（1）可扩展的高级分析，（2）AI，包括可解释的机器学习（ML），（3）用于网络安全的ML，（4）用于ML的网络安全（例如，对抗性ML），以及（5）安全区块链技术。这些模块化和混合课程的设计将结合基于研究的知识和创新技术。课程将以教师主导和学生主导两种学习形式提供，以研究这两种不同方法之间学习结果的差异。该项目将提供重要信息，说明提供跨学科网络安全课程的最佳方法，以及教育界如何有效地扩大网络安全教育，使其超越典型的课堂课程。项目小组将开展外联活动，以确保代表性不足的群体参与，并将通过在专业学会相关会议上举办讲习班传播调查结果。该项目得到了安全和值得信赖的网络空间（SaTC）计划的特别倡议的支持，以促进网络安全，人工智能和教育领域之间新的，以前未探索的合作。SATC计划与联邦网络安全研究和发展战略计划和国家隐私研究战略保持一致，以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NSF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。

In recent years, researchers have applied artificial intelligence (AI) to effectively solve important problems in cybersecurity. While significant research progress has been made in cybersecurity with the help of AI, there is a shortage of highly educated workers who can solve challenging problems at the intersection of AI and cybersecurity. This project will develop such a workforce by educating qualified individuals from diverse communities in cybersecurity and AI simultaneously. The project team will develop and deliver modular and project-based courses for graduate students that cover the basics of AI and cybersecurity using real-life problems. The development of innovative courses is intended to strengthen the student experience and to build a strong and diverse workforce in AI and cybersecurity that will fill the current voids in government, industry, and academia.The project team will develop five modular courses for graduate students: (1) Scalable Advanced Analytics, (2) AI including Explainable Machine Learning (ML), (3) ML for Cybersecurity, (4) Cybersecurity for ML (e.g., Adversarial ML), and (5) Secure Blockchain Technologies. The design of these modular and hybrid courses will incorporate research-based pedagogies and innovative technologies. Courses will be offered in both instructor-led and student-directed learning formats to study the differences in learning outcome, if any, between these two different approaches. This project will provide important information regarding optimal methods to deliver interdisciplinary cybersecurity curricula and how the education community can effectively broaden access to cybersecurity education beyond typical classroom courses. The project team will conduct outreach activities to ensure participation by underrepresented populations and will disseminate findings through workshops at relevant meetings of professional societies. 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.