EAGER: SaTC-EDU: Identifying Educational Conceptions and Challenges in Cybersecurity and Artificial Intelligence

EAGER：SaTC-EDU：确定网络安全和人工智能的教育理念和挑战

• 批准号: 2039445
• 负责人: Atul Prakash
• 金额: $ 30万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2039445&HistoricalAwards=false
• 关键词: EAGER; SaTC; EDU; Identifying; Educational

Artificial intelligence (AI) has significant applications to many data-intensive emerging domains such as automated vehicles, computer-assisted medical imaging, behavior analysis, user authentication, cybersecurity, and embedded systems for smart infrastructures. However, there are unanswered questions relating to trust in AI systems. There is increasing evidence that machine learning algorithms can be maliciously manipulated to cause misclassification and false detection of objects and speech. With the growing adoption of AI-based techniques, it is therefore important to teach students the skills needed to analyze vulnerabilities in AI-based systems and how such systems may fail, as well as how to mitigate such issues to help create more trustworthy AI-based systems. This project brings together experts from the areas of education, AI, and cybersecurity to identify challenges and potential solutions to teaching topics in trustworthy AI with the goal of evolving coursework that will appeal to, and engage, a diverse student body. It is critical to diversify the workforce operating at the intersection of cybersecurity and AI because AI-based systems can be prone to implicit vulnerabilities and blind spots due to imbalanced datasets or training methods that focus only on the overall accuracy of available datasets. The project team proposes to teach and study three courses at the intersection of cybersecurity and AI, including creating a new course on trustworthy AI. Coursework will address topics that will spur students to consider how segments of the population may be differentially impacted in areas such as authentication, privacy, and user safety. Learning science and educational psychology approaches (specifically focus groups and clinical interviews) will be used to identify learning and teaching challenges and to characterize conceptions and misconceptions. The project will produce five deliverables: model curricula at the crossroads of cybersecurity and AI; strategies for managing cross-disciplinarity in such curricula; characterizations of student concepts; identification of student learning challenges; and identification of new research directions in cybersecurity and AI. The findings and curricular ideas will be disseminated broadly. 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.

人工智能 (AI) 在许多数据密集型新兴领域具有重要应用，例如自动驾驶车辆、计算机辅助医学成像、行为分析、用户身份验证、网络安全和智能基础设施的嵌入式系统。 然而，与人工智能系统的信任有关的问题尚未得到解答。 越来越多的证据表明，机器学习算法可能被恶意操纵，导致对象和语音的错误分类和错误检测。因此，随着基于人工智能的技术的日益普及，教给学生分析基于人工智能的系统中的漏洞、此类系统可能如何失败以及如何缓解此类问题以帮助创建更值得信赖的人工智能所需的技能非常重要。为基础的系统。 该项目汇集了来自教育、人工智能和网络安全领域的专家，旨在确定可信人工智能教学主题的挑战和潜在解决方案，目标是不断发展吸引和吸引多元化学生群体的课程作业。使网络安全和人工智能交叉领域的劳动力多样化至关重要，因为由于数据集不平衡或只关注可用数据集整体准确性的培训方法，基于人工智能的系统很容易出现隐性漏洞和盲点。该项目团队建议教授和研究网络安全和人工智能交叉领域的三门课程，包括创建一门关于可信人工智能的新课程。课程作业将讨论一些主题，这些主题将促使学生考虑不同人群在身份验证、隐私和用户安全等领域可能受到的不同影响。将使用学习科学和教育心理学方法（特别是焦点小组和临床访谈）来识别学习和教学挑战并描述概念和误解。该项目将产生五项成果：网络安全和人工智能交叉点的模型课程；管理此类课程中跨学科的策略；学生概念的特征；识别学生的学习挑战；并确定网络安全和人工智能的新研究方向。研究结果和课程理念将得到广泛传播。该项目得到了安全可信网络空间 (SaTC) 计划特别倡议的支持，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。 SaTC 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，并被认为值得获得通过使用基金会的智力优势和更广泛的影响审查标准进行评估来提供支持。