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

基本信息

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

项目摘要

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.

国家关键基础设施的各个部门都希望将安全的人工智能（AI）应用到日常运营中，并从基于人工智能的决策工具和人工智能人系统中受益。这些结果需要对不同环境中人类行为的透彻理解。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。重要因素，例如混杂变量，常常被忽视。另外，重视学习进行相关性、关联性分析，而对学习因果性分析重视不够。该项目将开发和评估教育模块，帮助新一代工程和计算机科学（CS）学生开发现实的决策计算模型。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目标。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计算机科学学生如何准备通过计算方式学习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现实决策计算模型。其次，该项目将寻求了解如何开发网络安全和隐私方面的因果（与相关）模型。项目团队将为学生提供开发因果网络与传统相关网络的机会。基于这项研究的课程模块将在佐治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。