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.

AI和网络安全之间的相互作用引入了AI网络安全以及AI的网络安全方面的新机会和挑战。但是，典型的AI Currentulum中很少涵盖具有安全心态的AI网络基础结构（CI）的操作和配置。为了填补这一空白，该项目旨在开发动手培训材料，并为工程和科学相关学科的当前和未来研究人员提供指导的培训。通过将培训材料转换为课程课程，该项目旨在培训CI社区中的潜在网络基础设施专业人员，以与网络安全处理AI。该项目有潜力发展研究工作人员，并以安全心态运营AI网络基础设施，以满足CI促进的国家和经济需求和优先事项。该项目的目标是通过培训扩大采用高级网络基础设施。该项目开发了一种用于网络培养的整体技术方法：识别，应用和评估与定义明确的运营网络安全挑战密不可分的AI技术。该项目旨在开发一个基于码头的培训平台，该平台模拟和预配置各种方案，以支持网络安全的动手AI Cyber​​infrastructure操作。设计并集成到平台中，以帮助研究人员和教育工作者将三个级别的项目（探索性，核心和高级）进行设计，并将其开发到不同的教育和培训环境中。该项目使高级AI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心态整合起来，以促进跨学科和机构间研究合作。除了通过出版物和社交媒体的传播外，该项目的结果还有可能通过培训和共享“ and for Cyber​​security and at Cyber​​surity”课程课程来使更大的网络基础设施社区及其他地区受益。该项目由OAC和Cyber​​Corps计划共同资助。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响审查标准来评估被认为是宝贵的支持。