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

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:
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
项目状态:
未结题
起止时间:
2021-05-01 至 2025-04-30

项目摘要

项目成果

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中文摘要
翻译
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训练有素的劳动力。课程和研讨会正在兴起,以满足这一需求,但还没有出版的作品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点的劳动力。该项目通过确定劳动力需求和开发解决方案来解决可能阻止广泛参与AI增强的网络安全的学习障碍,解决了我们对如何准备劳动力将AI应用于网络安全问题的理解方面的差距。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的网络安全课程,并在人工智能,网络安全和教育的交叉点上贡献新知识。该项目将通过与行业专家的访谈来确定人工智能增强的网络安全的劳动力培训需求。这将为硕士和高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。实践课程将作为一个测试平台,以确定关键的概念挑战,先决条件和人工智能增强网络安全的令人信服的例子。该课程将培训华盛顿大学博瑟尔的学生掌握关键的人工智能增强的网络安全技能。此外,该项目旨在确定扩大人工智能和网络安全交叉领域参与的机会。更好地了解计算专业如何看待人工智能,网络安全以及两者的交叉点的课程和职业生涯,可以为扩大人工智能增强的网络安全的参与提供信息。这种跨学科的合作也将使项目团队做好准备,从事人工智能和网络安全交叉领域的教育研究。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。
英文摘要
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.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
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
影响因子: --
作者: [Ojha, Vidushi, Perdriau, Christopher, Lagesse, Brent, Lewis, Colleen M.]
通讯作者: Lewis, Colleen M.
IRES Track 1: Secure Crowdsensing for Improving Smart City Applications
  • 批准号:
    1853953
  • 项目类别:
    Standard Grant
  • 资助金额:
    $29.9万
  • 财政年份:
    2019
  • 负责人:
    Brent Lagesse
  • 依托单位:
EDU: Enhancing Cybersecurity Education for Native Students Using Virtual Laboratories
  • 批准号:
    1419313
  • 项目类别:
    Standard Grant
  • 资助金额:
    $29.3万
  • 财政年份:
    2014
  • 负责人:
    Brent Lagesse
  • 依托单位:
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)