EAGER: SaTC-EDU: Cybersecurity Education in the Age of Artificial Intelligence: A Novel Proactive and Collaborative Learning Paradigm

EAGER：SaTC-EDU：人工智能时代的网络安全教育：一种新颖的主动协作学习范式

• 批准号: 2114974
• 负责人: Jin Wei-Kocsis
• 金额: $ 29.99万
• 依托单位: Purdue 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 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2114974&HistoricalAwards=false
• 关键词: EAGER; SaTC; EDU; Cybersecurity; Education

Artificial intelligence (AI) techniques, especially machine learning (ML), show great promise for improving quality of life. However, recent research has demonstrated that AI techniques can be manipulated, evaded, and misled. While progress has been made to better understand the trustworthiness and security of AI techniques, little has been done to translate this knowledge to education and training. There is a critical need to foster a qualified cybersecurity workforce that understands the usefulness, limitations, and best practices of AI technologies in the cybersecurity domain. This project will address this important issue by designing and implementing a virtual, proactive, and collaborative learning paradigm that can engage learners with different backgrounds. The approach will benefit a wide range of learners, especially underrepresented students. It will also help the general public understand the security implications of AI. This project has the ability to transform education at the intersection of cybersecurity and AI/ML; shed light on explainable AI in cybersecurity; and grow a cybersecurity workforce that possesses AI competencies. Products, including the research findings and curriculum, will be disseminated through a variety of mechanisms, such as workshops, peer-reviewed conferences, and journals. This project builds research and education capacity through the formation of a multidisciplinary team with expertise in cybersecurity, AI, and statistics. The team will systematically investigate two cohesive research and education goals. First, an immersive learning environment will be developed to motivate students to explore AI/ML development in the context of real-world cybersecurity scenarios by constructing learning models with tangible objects. The proposed learning environment enables an AI/ML mechanism that will provide personalized explanations on the AI/ML outputs by considering the distinct background knowledge of the individual learners. Second, the team will design a proactive education paradigm encourages students to collaboratively identify new AI/ML-specific threats in the cybersecurity domain and develop innovative and trustworthy AI/ML solutions. The learning paradigm will ultimately enable effective retention and transfer of multidisciplinary AI-cybersecurity knowledge.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）技术，尤其是机器学习（ML），在提高生活质量方面展现出巨大的前景。然而，最近的研究表明，人工智能技术可以被操纵，逃避和误导。虽然在更好地理解人工智能技术的可信度和安全性方面取得了进展，但在将这些知识转化为教育和培训方面却做得很少。我们迫切需要培养一支合格的网络安全人才队伍，他们了解人工智能技术在网络安全领域的有用性、局限性和最佳实践。这个项目将通过设计和实施一个虚拟的，主动的，协作的学习模式，可以吸引不同背景的学习者来解决这个重要的问题。这种方法将使广泛的学习者受益，特别是代表性不足的学生。它还将帮助公众了解人工智能的安全影响。该项目有能力改变网络安全和AI/ML交叉点的教育;阐明网络安全中可解释的AI;并培养一支拥有AI能力的网络安全队伍。将通过讲习班、同行审查会议和期刊等各种机制传播研究成果和课程。该项目通过组建一个具有网络安全，人工智能和统计专业知识的多学科团队来建立研究和教育能力。该小组将系统地调查两个有凝聚力的研究和教育目标。首先，将开发一个沉浸式学习环境，通过构建具有有形对象的学习模型，激励学生在现实世界的网络安全场景中探索AI/ML开发。所提出的学习环境支持AI/ML机制，该机制将通过考虑单个学习者的不同背景知识来提供对AI/ML输出的个性化解释。其次，该团队将设计一个积极主动的教育模式，鼓励学生协作识别网络安全领域中新的AI/ML特定威胁，并开发创新和值得信赖的AI/ML解决方案。该学习范式最终将使多学科人工智能网络安全知识的有效保留和转移。该项目得到安全和可信网络空间（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的新的，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。

项目成果

Cybersecurity Education in the Age of Artificial Intelligence: A Novel Proactive and Collaborative Learning Paradigm

人工智能时代的网络安全教育：一种新颖的主动协作学习范式

• DOI: 10.1109/te.2023.3337337
• 发表时间: 2023
• 期刊: IEEE Transactions on Education
• 影响因子: 2.6
• 作者: Wei-Kocsis, Jin;Sabounchi, Moein;Mendis, Gihan J.;Fernando, Praveen;Yang, Baijian;Zhang, Tonglin
• 通讯作者: Zhang, Tonglin