课题基金 / 基金详情

NSF Convergence Accelerator Track G: Combating Vulnerability and Unawareness in 5G Network Security

NSF Convergence Accelerator Track G: Combating Vulnerability and Unawareness in 5G Network Security
NSF 融合加速器轨道 G:对抗 5G 网络安全中的漏洞和无意识
批准号:
2326898
负责人:
Taejoon Kim
金额:
$500.0万
依托单位国家:
美国
项目类别:
Cooperative Agreement
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-09-01 至 2025-08-31

项目摘要

项目成果

Taejoon Kim的其他基金

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中文摘要
翻译
可靠和高速率的5G无线接入已成为全球必需品;然而,美国在无线领导地位方面落在了后面,缺乏主要的无线电接入网络(RAN)或蜂窝网络制造商。此外,蜂窝网络不是为关键任务通信而设计的,并暴露了几个安全漏洞。因此,国防部(DoD)在将商业现成的5G产品和商业网络用于美国军事行动方面面临挑战。零信任X(ZTX)团队是5G和安全领域的跨学科专家联盟,将研究和开发一系列安全解决方案,以建立零信任链(ZTC),实现端到端的安全和保护,以可靠地使用5G网络用于国防部用例。拟议的努力将产生为美国工业界和国防部量身定做的知识和研究成果。此外,该项目将培训一支多样化的学生研究团队,并提供开源软件,以促进可移植性、可重复性,以及与该项目的其他Track G解决方案的集成。该项目的具体目标是开发ZTC软件,使军事小队能够使用高性能但往往不可信的5G网络在其行动中安全地分享态势感知。该软件解决方案利用5G标准的灵活性,在不同的网络节点和层实施创新的安全解决方案,使国防部运营商能够近乎实时地检测恶意实体,并建立通信机制,以防止访问或控制国防部流量。具体地说,通过与5G网络运营商的最低限度合作,ZTC解决方案的一部分利用Open-RAN(O-RAN)和5G核心中心方法进行实际威胁监控和缓解。这还得到了以设备为中心的安全增强的补充,以确保国防部设备也实施其自己的安全层,而不是仅依赖网络提供商的安全协议。ZTC有别于其他解决方案的六个关键特征:(I)它建立在开放式人工智能蜂窝(OAIC)平台上,通过RAN智能控制器开发O-RAN威胁监控和缓解;(Ii)它提供跨越5G RAN和核心的端到端安全切片;(Iii)它近乎实时地检测用户设备上的威胁;(Iv)它通过在应用层的创新而不是修改现有的5G物理层协议和算法来保护通信;(V)它确保位置隐私和对未知/意外的拒绝服务(DoS)攻击的弹性;以及(Vi)不需要修改公共5G/O-RAN网络和标准,只需要在5G用户设备和协作5G网络上安装低开销软件模块。ZTX团队的工作适用于商用和军用5G通信网络以及O-RAN。ZTX团队将首先在实验室规模的集成5G/O-RAN试验台上实施和试验性评估拟议的ZTC,然后在其他可用的试验台上实施和试验性评估,为商业过渡做准备。该团队将应用融合加速器的基本原理来促进合作伙伴关系,并开发可持续发展模式,其影响远远超出计划的第二阶段。该奖项反映了NSF的法定使命,并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,被认为值得支持。
英文摘要
Reliable and high-rate 5G wireless access has become a global necessity; however, the US has fallen behind in wireless leadership, lacking major radio access network (RAN) or cellular network manufacturers. Furthermore, cellular networks have not been designed for mission-critical communications and have exposed several security vulnerabilities. Consequently, the Department of Defense (DoD) faces challenges in using commercial off-the-shelf 5G products and commercial networks for US military operations. The Zero Trust X (ZTX) team, a consortium of interdisciplinary experts in the field of 5G and security, will research and develop a family of security solutions to establish a Zero Trust Chain (ZTC) that enables end-to-end security and protection for reliable use of 5G networks for DoD use cases. The proposed effort will generate knowledge and research outcomes tailored for use by US industry and DoD. Additionally, the project will train a diverse team of students in research and provide open-source software that facilitates portability, reproducibility, and integration with other Track G solutions of this program.The project's specific goal is to develop the ZTC software that enables military squads to securely share situational awareness in their operations using high-performance, yet often untrusted, 5G networks. The software solution leverages the flexibility of the 5G standard and implements innovative security solutions at different network nodes and layers to empower DoD operators to detect malicious entities in near-real time and establish communication mechanisms to prevent access to or control over DoD traffic. Specifically, through minimal cooperation with 5G network operators, part of the ZTC solution leverages Open-RAN (O-RAN) and 5G core-centric approaches for practical threat monitoring and mitigation. This is complemented by device-centric security enhancements to ensure that DoD devices also implement their own layer of security and do not solely depend on the security protocols of the network provider. Six key features set ZTC apart from other solutions: (i) it builds on the Open Artificial Intelligence Cellular (OAIC) platform for developing O-RAN threat monitoring and mitigation through RAN Intelligent Controllers; (ii) it offers end-to-end secure slicing across the 5G RAN and Core; (iii) it detects threats at user devices in near-real time; (iv) it protects communication through innovation at the application layer rather than modifying existing 5G physical layer protocols and algorithms; (v) it ensures location privacy and resiliency to unknown/unanticipated denial of service (DoS) attacks; and (vi) it does not require modifications to public 5G/O-RAN networks and standards, and only requires installation of low-overhead software modules on 5G user devices and cooperative 5G networks. The ZTX team's work is applicable to commercial and military 5G communication networks and to O-RAN. The ZTX team will implement and experimentally evaluate the proposed ZTC initially on a laboratory-scale integrated 5G/O-RAN testbed, and subsequently on other available testbeds to prepare for commercial transition. The team will apply Convergence Accelerator fundamentals to foster partnerships and to develop a sustainability model with an impact extending well beyond Phase 2 of the 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.
期刊论文(5)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1109/ieeeconf59524.2023.10476780
发表时间: 2023-10
期刊: 2023 57th Asilomar Conference on Signals, Systems, and Computers
影响因子: --
作者: [Dang Qua Nguyen;Taejoon Kim]
通讯作者: Dang Qua Nguyen;Taejoon Kim
DOI: 10.1109/jsac.2023.3336154
发表时间: 2023-01
期刊: IEEE Journal on Selected Areas in Communications
影响因子: 16.4
作者: [M. Oh;A. Das;Seyyedali Hosseinalipour;Taejoon Kim;D. Love;Christopher G. Brinton]
通讯作者: M. Oh;A. Das;Seyyedali Hosseinalipour;Taejoon Kim;D. Love;Christopher G. Brinton
Demo: SSxApp: Secure Slicing for O-RAN Deployments
演示:SSxApp:O-RAN 部署的安全切片
DOI: --
发表时间: 2023
期刊: MILCOM IEEE Military Communications Conference
影响因子: --
作者: [Moore, Joshua, Abdalla, Aly, Zhang, Minglong, Marojevic, Vuk]
通讯作者: Marojevic, Vuk
DOI: 10.1109/tvt.2023.3315325
发表时间: 2021-08
期刊: IEEE Transactions on Vehicular Technology
影响因子: 6.8
作者: [W. Zhang;Taejoon Kim]
通讯作者: W. Zhang;Taejoon Kim
Collaborative Research: NSF-AoF: CNS Core: Small: Towards Scalable and Al-based Solutions for Beyond-5G Radio Access Networks
GOALI: CNS: Medium: Communication-Computation Co-Design for Rural Connectivtiy and Intelligence under Nonuniformity: Modeling, Analysis, and Implementation
NSF Convergence Accelerator Track G: Combating Vulnerability and Unawareness in 5G Network Security: Signaling and Full-Stack Approach
海外基金