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），在改善生活质量方面表现出了巨大的希望。但是，最近的研究表明，可以操纵，逃避和误导AI技术。尽管已经取得了进步来更好地了解AI技术的可信度和安全性，但几乎没有将这些知识转化为教育和培训。迫切需要培养合格的网络安全劳动力，以了解网络安全域中AI技术的有用性，局限性和最佳实践。该项目将通过设计和实施虚拟，积极主动和协作学习范式来解决这一重要问题，该范式可以吸引具有不同背景的学习者。该方法将使广泛的学习者受益，尤其是代表性不足的学生。它还将帮助公众了解AI的安全含义。该项目有能力在网络安全和AI/ML的交汇处转变教育；阐明了可解释的网络安全性AI；并增加具有AI能力的网络安全劳动力。包括研究结果和课程在内的产品将通过各种机制，例如讲习班，经过同行评审的会议和期刊来传播。该项目通过组建具有网络安全，AI和统计学专业知识的多学科团队来建立研究和教育能力。团队将系统地研究两个凝聚力的研究和教育目标。首先，将开发一个沉浸式的学习环境，以激励学生在现实世界网络安全方案的背景下探索AI/ML的开发，通过构建具有切实对象的学习模型。提出的学习环境可以通过考虑各个学习者的独特背景知识来提供AI/ML机制，该机制将对AI/ML输出提供个性化的解释。其次，该团队将设计一个积极的教育范式，鼓励学生在网络安全领域中协作确定新的AI/ML特定威胁，并开发创新且值得信赖的AI/ML解决方案。学习范式最终将使多学科AI-Cyber​​security知识的有效保留和转移。该项目得到了对安全且可信赖的网络空间（SATC）计划的特别主动，以培养新的，以前没有开发的网络企业之间的合作，人工情报和教育和教育。 SATC计划与联邦网络安全研究与发展战略计划以及国家隐私研究策略保持一致，以保护和保留网络系统的社会和经济益处，同时确保安全和隐私。该奖项反映了NSF的法定任务，并认为通过基金会的知识分子和更广泛的影响，可以通过评估来进行评估，以审查Criteria。

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