Collaborative Research: CyberTraining: Pilot: Operationalizing AI/Machine Learning for Cybersecurity Training

合作研究：网络培训：试点：将人工智能/机器学习应用于网络安全培训

• 批准号: 2229975
• 负责人: Houbing Song
• 金额: $ 16万
• 依托单位: Embry-Riddle Aeronautical University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2023-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2229975&HistoricalAwards=false
• 关键词: Collaborative; Research; CyberTraining; Pilot; Operationalizing

The interplay between AI and cybersecurity introduces new opportunities and challenges in the cybersecurity of AI as well as AI for cybersecurity. However, operations and configurations of AI cyberinfrastructure (CI) with a security mindset are rarely covered in the typical AI curriculum. To fill this gap, this project intends to develop hands-on training materials and provide mentored training for current and future research workforce in engineering and science-related disciplines. By transforming and integrating training materials into a course curriculum, this project aims to train potential cyberinfrastructure professionals in the CI community at large to handle AI with and for cybersecurity. This project has the potential to develop the research workforce in operating AI cyberinfrastructure with a security mindset to meet the national and economical needs and priorities of CI advancement. This project’s goal is to broaden the adoption of advanced cyberinfrastructure through training. This project develops a holistic technical approach for cybertraining: to identify, apply, and evaluate AI techniques which are inextricably related to well-defined operational cybersecurity challenges. The project intends to develop a Docker-based training platform that simulates and pre-configures a variety of scenarios to support hands-on AI cyberinfrastructure operations in the context of cybersecurity. Three levels of projects (exploratory, core, and advanced) are designed and integrated into the platform to help researchers and educators customize and develop into different education and training environments. The project democratizes the access and adoption of advanced AI cyberinfrastructure, while integrating cyberinfrastructure skills with the security mindset to foster inter-disciplinary and inter-institutional research collaborations. In addition to the dissemination through publications and social media, the outcomes from this project have the potential to benefit the greater cyberinfrastructure community and beyond, through the training and the sharing of the "AI for and with cybersecurity" course curriculum. This project is jointly funded by OAC and the CyberCorps program.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.

人工智能与网络安全之间的相互作用为人工智能的网络安全以及人工智能的网络安全带来了新的机遇和挑战。然而，典型的人工智能课程很少涉及具有安全思维的人工智能网络基础设施（CI）的操作和配置。为了填补这一空白，该项目打算开发实践培训材料，并为工程和科学相关学科的当前和未来的研究人员提供指导培训。通过将培训材料转化并整合到课程中，该项目旨在培训CI社区中潜在的网络基础设施专业人员，以处理AI和网络安全。该项目有可能培养具有安全思维的人工智能网络基础设施运营研究人员，以满足国家和经济需求以及CI发展的优先事项。该项目的目标是通过培训扩大采用先进的网络基础设施。该项目为网络培训开发了一种整体技术方法：识别、应用和评估与明确定义的运营网络安全挑战有着千丝万缕的联系的人工智能技术。该项目旨在开发一个基于Docker的培训平台，模拟和预配置各种场景，以支持在网络安全背景下的人工智能网络基础设施操作。三个级别的项目（探索性，核心和高级）被设计并集成到平台中，以帮助研究人员和教育工作者定制和开发不同的教育和培训环境。该项目使先进的人工智能网络基础设施的访问和采用民主化，同时将网络基础设施技能与安全思维相结合，以促进跨学科和跨机构的研究合作。除了通过出版物和社交媒体进行传播外，该项目的成果还有可能通过培训和分享“人工智能促进网络安全”课程，使更广泛的网络基础设施社区及其他社区受益。该项目由OAC和CyberCorps计划共同资助。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。