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

合作研究：EAGER：SaTC-EDU：安全和隐私保护的网络安全自适应人工智能课程开发

• 批准号: 2039408
• 负责人: Kimmy Nimon
• 金额: $ 2.97万
• 依托单位: University of Texas at Tyler
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2039408&HistoricalAwards=false
• 关键词: Collaborative; Research; EAGER; SaTC; EDU

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.

近年来，研究人员应用了人工智能（AI）来有效解决网络安全问题的重要问题。尽管在AI的帮助下，尽管在网络安全方面取得了重大的研究进展，但缺乏受过良好教育的工人可以在AI和网络安全的交集中解决挑战性问题。该项目将通过同时教育来自不同社区的合格个人和AI的合格个人来发展这样的劳动力。项目团队将为研究生开发并提供基于项目的课程，并使用现实生活中的问题涵盖AI和网络安全的基础。创新课程的开发旨在增强学生的体验，并在AI和网络安全方面建立强大而多样化的员工队伍，以填补政府，行业和学术界的当前空白。项目团队将为研究生开发五个模块化课程，为研究生提供五个模块化课程：（1）可缩放的高级分析，（2）AIBECER，（2）AICER，（2）cyer（2）cyer（ML）（3）ML（ML）（3）ML（3）ML（3）ML（3） ML（例如对抗性ML）和（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教学法和创新技术。课程将以讲师为主导和指导的学习格式提供课程，以研究这两种不同方法之间学习成果（如果有的话）的差异。该项目将提供有关提供跨学科网络安全课程的最佳方法的重要信息，以及教育社区如何有效地扩大对网络安全教育的访问，超出典型的课堂课程。项目团队将进行外展活动，以确保人口不足的人群参与，并通过专业社会相关会议的研讨会来传播调查结果。该项目由安全且值得信赖的网络空间（SATC）计划提供支持，以促进网络安全，人工智能和教育领域之间的新，以前未开发的合作。 SATC计划与联邦网络安全研究与发展战略计划以及国家隐私研究策略保持一致，以保护和保留网络系统的社会和经济益处，同时确保安全和隐私。该奖项反映了NSF的法定任务，并认为通过基金会的知识分子和更广泛的影响，可以通过评估来进行评估，以审查Criteria。