EAGER: SaTC-EDU: Advancing Cybersecurity Education to Human-Level Artificial Intelligence

EAGER：SaTC-EDU：将网络安全教育推进到人类水平的人工智能

• 批准号: 2041788
• 负责人: Fariborz Farahmand
• 金额: $ 29.98万
• 依托单位: Georgia Tech Research Corporation
• 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=2041788&HistoricalAwards=false
• 关键词: EAGER; SaTC; EDU; Advancing; Cybersecurity

All sectors of the national critical infrastructure are expected to apply secure artificial intelligence (AI) in their daily operations, and benefit from AI-based decision-making tools and AI-human systems. These outcomes require a thorough understanding of human behavior in different environments. However, for mathematical convenience, existing cybersecurity education approaches assume humans always make rational decisions. Important factors, such as confounding variables, are often ignored. In addition, there is an emphasis on learning to conduct correlation and association analyses, and insufficient attention paid to learning causation analysis. This project will develop and evaluate educational modules that will prepare a new generation of engineering and computer science (CS) students to develop realistic computational models of decision-making. The proposed activities will advance cybersecurity education from association to causation analysis and contribute to the goal of achieving human-level AI. This project will address two fundamental challenges in cybersecurity, privacy, and AI education. First, the project will investigate how engineering and CS students can be prepared to learn cybersecurity and privacy behaviors computationally. Students will learn to apply advanced AI methods to develop realistic computational models of decision-making that address both affective and cognitive processes. Second, the project will seek to understand how causal (vs. correlative) models in cybersecurity and privacy can be developed. The project team will provide opportunities for students to develop causal networks vs. traditional correlation networks. Course modules based on this research will be implemented and evaluated in existing advanced undergraduate/graduate courses at the Georgia Institute of Technology. The project will assess the impact of these modules on students' understanding on the role of AI in addressing cybersecurity and privacy issues. 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.

预计国家关键基础设施的所有部门都将在日常运营中应用安全的人工智能（AI），并从基于AI的决策工具和人工智能系统中受益。这些结果需要对人类在不同环境中的行为有透彻的了解。然而，为了数学上的方便，现有的网络安全教育方法假设人类总是做出理性的决定。重要的因素，如混杂变量，往往被忽视。此外，还有一个重点是学习进行相关和关联分析，而学习因果分析重视不够。该项目将开发和评估教育模块，为新一代工程和计算机科学（CS）学生开发决策的现实计算模型做好准备。拟议的活动将推动网络安全教育从关联到因果分析，并有助于实现人类水平的人工智能。该项目将解决网络安全、隐私和人工智能教育方面的两个基本挑战。首先，该项目将调查工程和CS学生如何准备学习计算网络安全和隐私行为。学生将学习应用先进的人工智能方法来开发解决情感和认知过程的决策的现实计算模型。其次，该项目将寻求了解如何在网络安全和隐私中开发因果（与相关）模型。项目团队将为学生提供机会，开发因果网络与传统的相关网络。基于这项研究的课程模块将在格鲁吉亚理工学院现有的高级本科/研究生课程中实施和评估。该项目将评估这些模块对学生理解人工智能在解决网络安全和隐私问题中的作用的影响。该项目得到了安全和值得信赖的网络空间（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

A System Engineering Approach to AI Security and Safety

人工智能安全的系统工程方法

• DOI: 10.1109/mc.2023.3310219
• 发表时间: 2023
• 期刊: Computer
• 影响因子: 2.2
• 作者: Farahmand, Fariborz

Quantum Cognition: A Cognitive Architecture for Human-AI and In-Memory Computing

量子认知：人类人工智能和内存计算的认知架构

• DOI: 10.1109/mc.2023.3242056
• 发表时间: 2023
• 期刊: Computer
• 影响因子: 2.2
• 作者: Farahmand, Fariborz

Integrating Cybersecurity and Artificial Intelligence Research in Engineering and Computer Science Education

将网络安全和人工智能研究融入工程和计算机科学教育

• DOI: 10.1109/msec.2021.3103460
• 发表时间: 2021
• 期刊: IEEE Security & Privacy
• 影响因子: 1.9
• 作者: Farahmand, Fariborz