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先进水平来服务于国家利益。国家网络基础设施容易受到各种网络威胁和危害的影响。网络威胁情报数据可以洞察网络攻击，并提供主动安全的机会。主动网络安全已经变得依赖于人工智能，因此网络安全从业者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、教育和行为科学的研究，研究以证据为基础的知识生成方法，以实现强调人工智能-人类团队的网络安全教育。调查人员将研究人工智能与人类团队的信任与合作，以产生知识，为未来人工智能与网络安全交叉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，包括：1)支持人工智能的防御模拟套件（AI- edsims），为学生和网络安全专业人员提供实践学习；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，重点是人工智能和人的团队合作，积极开展网络安全实践，从而改变本科教育；3)人工智能网络安全教育的新知识，因为它与人工智能-人类团队有关，从而更好地理解信任与合作在人工智能-人类团队中的作用。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。通过参与学生学习轨道，该计划支持有前途的实践和工具的创建，探索和实施。该奖项反映了美国国家科学基金会的法定使命，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.