A Novel AI-Human Teaming Approach to Trust and Cooperation in AI-Cybersecurity Education

该项目旨在通过提高网络安全教育的最新水平来服务于国家利益。国家网络基础设施易受各种网络威胁和危害的影响。网络威胁情报数据可以让您深入了解网络攻击，并提供主动保护的机会。主动网络安全已经变得依赖于人工智能，这使得网络安全从业人员必须同时了解网络安全和人工智能。该项目将结合人工智能，网络安全，教育和行为科学的联合收割机研究，以调查基于证据和知识生成的方法来进行网络安全教育，强调人工智能-人类团队。研究人员将研究人工智能-人类团队中的信任与合作，以产生知识，为未来人工智能和网络安全交叉点的教育工作提供信息。该项目将通过三个目标推进人工智能，网络安全和行为科学领域的教育知识，从而产生1）AI支持的防御模拟套件（AI-EDSimS），使学生和网络安全专业人员能够动手学习，2）一门关于人工智能和网络安全的新课程，通过整合这两门学科来改变本科教育，重点是人工智能-人类团队进行积极的网络安全实践，3）人工智能网络安全教育的新知识，因为它与人工智能团队有关，从而提高了对人工智能团队中信任与合作作用的理解。NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生STEM教育的有效性。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。

This project aims to serve the national interest by improving the state-of-the-art in cybersecurity education. The national cyberinfrastructure is vulnerable to a wide range of cyberthreats and hazards. Cyberthreat intelligence data gives insight into a cyberattack and provides an opportunity to become proactively secure. Proactive cybersecurity has become dependent upon AI, making it essential that cybersecurity practitioners gain an understanding of both cybersecurity and AI. This project will combine research in AI, cybersecurity, education, and behavior science to investigate evidence-based and knowledge-generating approaches to cybersecurity education that emphasizes AI-human teams. The investigators will study trust and cooperation in AI-human teams to generate knowledge that will inform future educational efforts that lie at the intersection of AI and cybersecurity.This project will advance educational knowledge in the fields of AI, cybersecurity, and behavior science through three objectives, resulting in 1) AI-Enabled Defense Simulation Suite (AI-EDSimS), enabling hands-on learning for students and cybersecurity professionals, 2) a new course on AI and Cybersecurity transforming undergraduate education by integrating the two subjects with a focus on AI-human teaming for proactive cybersecurity practice, and 3) new knowledge in AI-Cybersecurity education as it relates to AI-human teaming, leading to improved understanding of the role of trust and cooperation in AI-human teams. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.