Collaborative Research: EAGER: SaTC-EDU: Artificial Intelligence-Enhanced Cybersecurity: Workforce Needs and Barriers to Learning

协作研究：EAGER：SaTC-EDU：人工智能增强的网络安全：劳动力需求和学习障碍

• 批准号: 2113954
• 负责人: Brent Lagesse
• 金额: $ 13.13万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2113954&HistoricalAwards=false
• 关键词: Collaborative; Research; EAGER; SaTC; EDU

The intersection of artificial intelligence (AI) and cybersecurity is emerging as an important field to ensure the integrity of the economy and critical infrastructure. Industry and government organizations require a workforce that is well-trained in both AI and cybersecurity. Courses and workshops are emerging to meet this need, but there is no published work addressing the content that needs to be taught and how to teach that content to develop a workforce at the intersection of AI and cybersecurity. This project addresses the gap in our understanding of how to prepare the workforce to apply AI to problems in cybersecurity by identifying workforce needs and developing solutions to learning barriers that could prevent broad participation in AI-enhanced cybersecurity. The project will create and disseminate an AI-enhanced cybersecurity course for advanced undergraduate and master's students and contribute new knowledge at the intersection of AI, cybersecurity, and education.This project will identify workforce training needs for AI-enhanced cybersecurity through interviews with industry experts. This will inform the development of a course for master's and advanced undergraduate students that addresses gaps in existing cybersecurity curricular frameworks. The hands-on course will serve as a testbed to identify key conceptual challenges, prerequisites, and compelling examples of AI-enhanced cybersecurity. The course will train students at the University of Washington Bothell in crucial AI-enhanced cybersecurity skills. Additionally, the project seeks to identify opportunities to broaden participation at the intersection of AI and cybersecurity. A better understanding of how computing majors perceive courses and careers in AI, cybersecurity, and the intersection of the two can inform efforts to broaden participation in AI-enhanced cybersecurity. This interdisciplinary collaboration will also prepare the project team to engage in education research at the intersection of AI and cybersecurity. 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.

人工智能（AI）和网络安全的交叉正在成为确保经济和关键基础设施完整性的重要领域。行业和政府组织需要一支在人工智能和网络安全方面接受过良好培训的员工队伍。为了满足这一需求，课程和研讨会不断涌现，但还没有发表的著作来解决需要教授的内容以及如何教授这些内容以培养人工智能和网络安全交叉领域的劳动力。该项目通过确定劳动力需求并开发解决可能阻碍广泛参与人工智能增强网络安全的学习障碍的解决方案，解决了我们对如何准备劳动力将人工智能应用于网络安全问题的理解差距。该项目将为高年级本科生和硕士生创建和传播人工智能增强网络安全课程，并在人工智能、网络安全和教育的交叉领域贡献新知识。该项目将通过采访行业专家来确定人工智能增强网络安全的劳动力培训需求。这将为硕士和高年级本科生课程的开发提供信息，以解决现有网络安全课程框架中的差距。该实践课程将作为一个测试平台，以确定人工智能增强网络安全的关键概念挑战、先决条件和令人信服的示例。该课程将为华盛顿大学博塞尔分校的学生提供关键的人工智能增强网络安全技能的培训。此外，该项目还寻求寻找机会扩大人工智能和网络安全交叉领域的参与。更好地了解计算机专业的学生如何看待人工智能、网络安全以及两者的交叉领域的课程和职业，可以为扩大人工智能增强网络安全的参与提供信息。这种跨学科合作还将帮助项目团队做好参与人工智能和网络安全交叉领域的教育研究的准备。该项目得到了安全可信网络空间 (SaTC) 计划特别倡议的支持，旨在促进网络安全、人工智能和教育领域之间新的、以前未探索过的合作。 SaTC 计划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相一致，旨在保护和维护网络系统不断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，并被认为值得获得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来提供支持。

项目成果

Computing Specializations: Perceptions of AI and Cybersecurity Among CS Students

计算机专业：计算机科学学生对人工智能和网络安全的看法

• DOI: 10.1145/3545945.3569782
• 发表时间: 2023
• 期刊: Proceedings of the 54th ACM Technical Symposium on Computer Science Education
• 作者: Ojha, Vidushi;Perdriau, Christopher;Lagesse, Brent;Lewis, Colleen M.
• 通讯作者: Lewis, Colleen M.