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: 2039434
• 负责人: Lin Lipsmeyer
• 金额: $ 3.02万
• 依托单位: University of North Texas
• 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 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2039434&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，研究人员应用人工智能(AI)有效解决了网络安全中的重要问题。尽管在人工智能的帮助下，网络安全方面取得了重大研究进展，但在人工智能和网络安全的交叉点上，缺乏受过高等教育的工作者，他们能够解决具有挑战性的问题。该项目将通过同时教育来自不同社区的合格个人了解网络安全和人工智能来培养这样一支队伍。该项目团队将为研究生开发和提供基于项目的模块化课程，涵盖使用现实生活问题的人工智能和网络安全的基础知识。该项目团队将为研究生开发五门模块课程：(1)可扩展的高级分析，(2)包括可解释机器学习(ML)的人工智能，(3)网络安全的ML，(4)ML的网络安全，以及(5)安全区块链技术。这些单元课程和混合课程的设计将纳入以研究为基础的教学方法和创新技术。课程将以教师指导和学生指导两种形式提供，以研究这两种不同方法在学习结果上的差异。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，以及教育界如何有效地扩大获得网络安全教育的机会，使之超越典型的课堂课程。项目小组将开展外联活动，以确保代表人数不足的人口参与，并将通过在专业协会的有关会议上举办讲习班来传播调查结果。该项目得到了安全和值得信赖的网络空间(SATC)计划的一项特别倡议的支持，该计划旨在促进网络安全、人工智能和教育领域之间新的、以前从未探索过的合作。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智力优势和更广泛的影响审查标准进行评估，被认为值得支持。