Education DCL: EAGER: An Embedded Case Study Approach for Broadening Students' Mindset for Ethical and Responsible Cybersecurity

教育 DCL：EAGER：一种嵌入式案例研究方法，用于拓宽学生道德和负责任的网络安全思维

• 批准号: 2335636
• 负责人: Aditya Johri
• 金额: $ 29.95万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2335636&HistoricalAwards=false
• 关键词: Education; DCL; EAGER; Embedded; Case

The increasing use of AI-enabled technologies in social domains poses safety and security risks that future cybersecurity professionals will need to address. Importantly, many of these risks go beyond narrow notions of robustness against attack to include concerns about misuse, unintended consequences, fairness across users, and other possible harms that happen when technologies are broadly used in society. This raises the need for future cybersecurity professionals to be aware of these harms and to consider ethics and responsibility of the systems they secure. This project's goal is to help students develop an ethical and responsible mindset towards cybersecurity topics, focusing on technologies that use artificial intelligence (AI) in security and privacy use cases. To do this the project team will develop a series of case studies of AI-enabled technologies designed for social problems, helping students reason about aspects of the design that can raise or mitigate security and privacy risks. The cases will be designed to appear in a series of undergraduate and graduate cybersecurity-related courses, with the idea that repeated exposure to these topics will make ethical considerations an integral part of the security curriculum, and that seeing them in different contexts will reinforce student learning and prepare students to transfer these mindsets and skills across contexts as they enter the security workforce.Using prior research on situated learning and perspectival thinking, the project team will create a series of four role-play-based case studies that highlight different social and ethical risks that often arise around AI technologies designed for security-related problems. Role-play based methods are an effective pedagogical technique for learning and perspective-taking; the team plans to combine them with a concept map-based assessment approach that is well-suited for the kind of longitudinal assessment that will be needed for a multi-course curriculum effort. Further, the concept map elicitation will be grounded in common security standards and rubrics, tightening the connection between the role-playing exercises and the security workforce development goals of the project. Topics will be chosen to highlight different areas of cybersecurity, different social contexts, and different risks; the current plan includes incorporating cases that involve automated video monitoring for surveillance, privacy of smart home devices, and algorithmic evaluation of candidates for jobs. Overall, the project will develop a validated curriculum for increasing ethical responsibility in the future cybersecurity workforce; the curriculum development and assessment methods are also intended to be easily adaptable to other educational domains and problems.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.

在社会领域中越来越多地使用人工智能技术带来了未来网络安全专业人员需要解决的安全风险。重要的是，其中许多风险超出了针对攻击的稳健性的狭隘概念，还包括对滥用、意外后果、用户之间的公平性以及技术在社会广泛使用时可能发生的其他危害的担忧。这要求未来的网络安全专业人员意识到这些危害，并考虑他们所保护的系统的道德和责任。 该项目的目标是帮助学生培养对网络安全主题的道德和负责任的心态，重点关注在安全和隐私用例中使用人工智能 (AI) 的技术。为此，项目团队将开发一系列针对社会问题的人工智能技术案例研究，帮助学生推理设计中可能增加或减轻安全和隐私风险的方面。这些案例将出现在一系列本科生和研究生网络安全相关课程中，其理念是，反复接触这些主题将使道德考虑成为安全课程不可或缺的一部分，并且在不同的背景下看到它们将增强学生的能力。学习并准备学生在进入安全队伍时跨环境转移这些心态和技能。利用先前对情境学习和透视思维的研究，项目团队将创建一系列四个基于角色扮演的案例研究，突出不同的社会和人工智能技术经常出现的道德风险专为安全相关问题而设计。基于角色扮演的方法是一种有效的学习和观点采择的教学技术；该团队计划将它们与基于概念图的评估方法相结合，该方法非常适合多课程课程工作所需的纵向评估。此外，概念图启发将以通用安全标准和规则为基础，加强角色扮演练习与项目安全劳动力发展目标之间的联系。选择的主题将突出网络安全的不同领域、不同的社会背景和不同的风险；当前的计划包括纳入涉及自动视频监控、智能家居设备隐私以及求职者算法评估等案例。总体而言，该项目将开发一套经过验证的课程，以增强未来网络安全劳动力的道德责任；课程开发和评估方法也旨在轻松适应其他教育领域和问题。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。