EAGER: SaTC-EDU: Transformative Educational Approaches to Meld Artificial Intelligence and Cybersecurity Mindsets

EAGER：SaTC-EDU：融合人工智能和网络安全思维的变革性教育方法

• 批准号: 2115025
• 负责人: Drew Springall
• 金额: $ 29.99万
• 依托单位: Auburn University
• 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 2024-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2115025&HistoricalAwards=false
• 关键词: EAGER; SaTC; EDU; Transformative; Educational

Society is becoming increasingly dependent on technology that is susceptible to abuse by bad actors. Artificial Intelligence (AI) and cybersecurity are, like much of computer science, extremely technical fields that continue to advance at rapid rates both in knowledge and application. Computer science often allows a small team to leverage its members' expertise through the use of plug-and-play solutions that require little or no user intervention. In contrast, it has become obvious that reliance on a limited number of highly skilled people does not work as well for cybersecurity . This inadequacy appears to be addressable through the application of AI concepts and by training individuals who are expert in both AI and cybersecurity. However, the amount of time, focus, and effort required to become highly proficient in both AI and cybersecurity fields is a significant barrier to this solution. This project strives to explore potentially transformative educational approaches in order to prepare a more robust workforce at the intersection of AI and cybersecurity. Specifically, the project team proposes a collaborative, group-based, and hands-on course that combines students with a specific interest and existing background in either the AI or cybersecurity domain with students with the complementary background. This educational approach will produce students who share a combined AI and cybersecurity mindset.The fundamental assumption of this project is that students will rarely need to apply a deep, technical understanding of the AI field within the cybersecurity domain. As such, a more viable and succinct approach to producing a workforce competent in both domains is to focus on expanding students’ toolkits and providing them reference-anchors. This approach will enable students to more efficiently collaborate with domain-specific experts and across domain boundaries when they enter the workforce. In order to explore this approach, the project team proposes to develop a course directed at students with backgrounds in AI or cybersecurity. The course will combine elements from problem-based learning , studio-based learning, and group-based learning. This approach will cultivate students with a melded AI and cybersecurity mindset even though they may lack technical depth in their non-focus domain. This mindset or awareness will prepare these students to enter the workforce and collaborate across technical disciplines. While a future goal may be combined AI and cybersecurity “natives” it is important first to evaluate the more easily attainable option of instilling technical awareness and a multi-perspective approach. 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.

社会越来越依赖容易被不良行为者滥用的技术，而网络安全与计算机科学的许多领域一样，都是在知识和应用方面不断快速发展的技术领域。允许小团队通过使用很少或不需要用户干预的即插即用解决方案来利用其成员的专业知识。相比之下，依赖有限数量的高技能人员显然是行不通的。对于网络安全而言，这种不足似乎可以通过解决。然而，要高度精通人工智能和网络安全领域所需的时间、精力和精力是该解决方案的一个重大障碍。致力于探索潜在的变革性教育方法，以便在人工智能和网络安全的交叉领域培养更强大的劳动力。具体来说，项目团队提出了一种协作、基于小组的实践课程，将具有特定兴趣和现有知识的学生结合起来。具有人工智能或网络安全领域背景的学生具有互补性这种教育方法将培养具有人工智能和网络安全综合思维的学生。该项目的基本假设是学生很少需要对网络安全领域的人工智能领域有深入的技术理解。培养在这两个领域都能胜任的劳动力的更可行和简洁的方法是专注于扩展学生的工具包并为他们提供参考锚点。这种方法将使学生在进入时能够与特定领域的专家更有效地跨领域合作。劳动力。为了探索这种方法，该项目团队建议针对具有人工智能或网络安全背景的学生开发一门课程，该课程将结合基于问题的学习、基于工作室的学习和基于小组的学习的元素，这种方法将培养具有融合人工智能和网络安全思维的学生。尽管他们在非重点领域可能缺乏技术深度，但这种心态或意识将使这些学生为进入劳动力市场并跨技术学科进行协作做好准备。虽然未来的目标可能是将人工智能和网络安全“本地人”结合起来，但首先重要的是评估更容易实现的选项灌输技术意识和多视角方法 该项目得到了安全可信网络空间 (SaTC) 计划的特别倡议的支持，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。该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，并被认为值得通过以下方式获得支持：评估利用基金会的智力优势和更广泛的影响审查标准。