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.

社会越来越依赖于容易被不良行为者滥用的技术。人工智能（AI）和网络安全与许多计算机科学一样，都是技术性极强的领域，在知识和应用方面都在快速发展。计算机科学通常允许一个小团队通过使用即插即用解决方案来利用其成员的专业知识，这些解决方案几乎不需要用户干预。相比之下，很明显，依赖数量有限的高技能人员并不能很好地促进网络安全。这种不足似乎可以通过应用人工智能概念和培训人工智能和网络安全专家来解决。然而，在人工智能和网络安全领域高度精通所需的时间、精力和精力是该解决方案的一个重大障碍。该项目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点准备一支更强大的劳动力队伍。具体来说，项目团队提出了一个协作的，基于小组的和实践的课程，将具有特定兴趣的学生和在人工智能或网络安全领域的现有背景与具有互补背景的学生相结合。 这种教育方法将培养学生谁分享 结合人工智能和网络安全的心态。这个项目的基本假设是，学生将很少需要应用在网络安全领域的人工智能领域的深刻的技术理解。因此，培养在这两个领域都有能力的劳动力的一个更可行和简洁的方法是注重扩大学生的工具包，并为他们提供参考锚。 这种方法将使学生能够更有效地与特定领域的专家合作，并在进入劳动力市场时跨越领域界限。在 为了探索这种方法，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。本课程将结合联合收割机元素，从基于问题的学习，基于工作室的学习，和基于小组的学习。 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，即使他们可能在非重点领域缺乏技术深度。这种心态或意识将为这些学生进入劳动力市场和跨技术学科合作做好准备。虽然未来的目标可能是将人工智能和网络安全“原生”结合起来，但首先必须评估更容易实现的灌输技术意识和多视角方法的选择。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。