Collaborative Research: SaTC: EDU: A Comprehensive Training Program of AI for 5G and NextG Wireless Network Security

合作研究：SaTC：EDU：5G 和 NextG 无线网络安全人工智能综合培训项目

• 批准号: 2321271
• 负责人: Shangqing Zhao
• 金额: $ 20万
• 依托单位: University of Oklahoma Norman Campus
• 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: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2321271&HistoricalAwards=false
• 关键词: Collaborative; Research; SaTC; EDU; Comprehensive

The emergence of 5G and next-generation (NextG) networks is transforming our lives into a new cyber era, featuring high connectivity and intensive data exchange. Such a highly connected world poses security and privacy challenges (e.g., how to safeguard sensitive data and ensure individual privacy). Traditional wireless network security designs may not adequately address these challenges, due to the complexity of handling a large amount of operational data. Recently, significant research efforts have been focused on adopting artificial intelligence (AI) techniques for 5G and NextG security because of their efficiency and capability of processing a variety of complex data to achieve intelligent functionalities. The future workforce needs comprehensive, coherent training in the intersection of 5G/NextG, security, and AI to gain a fundamental understanding of deploying AI techniques for wireless network security. This project aims to fill an essential educational gap between wireless network security and AI techniques by creating educational materials and training projects to train the future workforce in AI for 5G/NextG security. The project team will develop two major types of educational materials: (i) curriculum modules and (ii) project-based training. The lab-based curriculum modules for AI in 5G/NextG security will consist of three categories: physical layer, medium access control (MAC) and network layers, and network applications. In each module, state-of-the-art wireless equipment will be leveraged to create a real-world experiment-in-the-loop learning experience for students to observe and understand the advantages of AI for 5G/NextG security. Project-based training for students to will allow them to gain hands-on experience in developing and evaluating AI techniques to improve wireless network security. This project will enable various broader impacts, including undergraduate student training opportunities, openly disseminated training materials, and outreach activities.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.

5G和下一代（NextG）网络的出现将我们的生活转变为新的网络时代，具有高连通性和密集的数据交流。如此高度联系的世界构成了安全性和隐私挑战（例如，如何保护敏感数据并确保个人隐私）。由于处理大量操作数据的复杂性，传统的无线网络安全设计可能无法充分解决这些挑战。最近，由于它们具有处理各种复杂数据以实现智能功能的效率和能力，因此重大研究工作集中在为5G和NextG安全采用人工智能（AI）技术。未来的劳动力需要在5G/NextG，Security和AI的交集中进行全面，连贯的培训，以获得对为无线网络安全部署AI技术的基本了解。该项目旨在通过创建教育材料和培训项目来培训AI中的未来劳动力，以填补无线网络安全和AI技术之间的基本教育差距，以获得5G/NEXTG安全。项目团队将开发两种主要类型的教育材料：（i）课程模块和（ii）基于项目的培训。 5G/NEXTG安全性AI的基于实验室的课程模块将包括三个类别：物理层，中访问控制（MAC）和网络层以及网络应用程序。在每个模块中，将利用最先进的无线设备来创建一个现实世界中的实验，以供学生观察和理解AI在5G/NEXTG安全性方面的优势。基于项目的学生培训将使他们能够获得开发和评估AI技术以提高无线网络安全性的动手经验。该项目将带来各种更广泛的影响，包括大学生培训机会，公开传播培训材料以及外展活动。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估评估标准来通过评估来支持的。