NSF Convergence Accelerator Track G: Combating Vulnerability and Unawareness in 5G Network Security: Signaling and Full-Stack Approach

NSF 融合加速器轨道 G:对抗 5G 网络安全中的漏洞和无意识:信令和全栈方法

基本信息

  • 批准号:
    2226447
  • 负责人:
  • 金额:
    $ 75万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-07-15 至 2024-06-30
  • 项目状态:
    已结题

项目摘要

Over the last ten years, 5G research and network deployments have engendered significant economic development and greatly improved lives around the world. At the same time, the Department of Defense (DoD) has made significant efforts to leverage commercial investments made in 5G networks. The push for DoD to rely heavily on 5G commercial systems is, however, problematic because commercial networks are not designed for many of the adversarial settings and electronic warfare (EW) scenarios common in military-hardened networks. Academic research must play an important role in addressing fundamental security challenges arising from the vulnerabilities and design weaknesses of 5G networks. Such challenges manifest themselves in major threats that threaten confidentiality, integrity, and availability of 5G networks such as eavesdropping on messages, spoofing and man-in-the-middle attacks, distributed denial of service (DDoS), and downgrading the service from 5G to 3G/2G. Historically, however, many of the security-related and adversarial problems common to DoD have been viewed as strictly outside of the academic research purview. The proposed project aims to change this by building upon the momentum to accelerate academic and industry research into secure beyond-5G wireless networks. The team is joining forces from academia, industry, and government with the focus on consolidating the ongoing 5G security-related research efforts of its members. The project will also contribute to workforce development by creating research experiences, involving both theory and experiments, for a diverse team of both undergraduate and graduate students. The proposed research has three unique attributes that enable Zero Trust solutions: (a) Particular focus on signal/waveform level and 5G radio access network (RAN) security; (b) Fine-granular data-plane and control-plane threat detection, tracking, and defense mechanisms; and (c) Integration and evaluation via full-stack, Open RAN/Mobile Core testbed. DoD applications are the main motivation for the proposed solutions. To both narrow the scope of the efforts and make it more grounded, the proposed research will be organized across the following three interwoven aspects: (i) The modeling of threats at the user equipment (UE), RAN, Enhanced Data for Global Evolution (EDGE), backhaul, and 5G packet core levels to understand how suboptimal 5G networks are; (ii) The design of threat detection, tracking, and protection algorithms/mechanisms that effectively modify signaling at the 5G RAN and the software functions/protocols at the 5G Core for granular access control and encryption; and (iii) Formal verification of the various security requirements of service-based architecture in the context of 5G RAN, Core, and Internet Edge that use existing and novel programmable hardware. The level of visibility and controllability that this project enables would allow the 5G service-based architectures to adapt themselves quickly to make way for the military and other critical services in a secure and timely manner - similar to how cars make way for ambulances and fire trucks on the highways, sharing the same road infrastructure.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.
在过去的十年中,5G研究和网络部署带来了重大的经济发展,极大地改善了世界各地的生活。与此同时,美国国防部(DoD)也做出了巨大努力,以利用5G网络的商业投资。然而,推动国防部严重依赖5G商用系统是有问题的,因为商用网络并不是为军事强化网络中常见的许多对抗性环境和电子战(EW)场景而设计的。学术研究必须在解决5G网络的脆弱性和设计弱点所带来的基本安全挑战方面发挥重要作用。这些挑战体现在威胁5G网络机密性、完整性和可用性的主要威胁中,例如窃听消息、欺骗和中间人攻击、分布式拒绝服务(DDoS)以及将服务从5G降级到3G/2G。然而,从历史上看,国防部常见的许多与安全相关的问题和对抗性问题一直被视为严格超出了学术研究的范围。拟议的项目旨在通过加速学术和行业研究以实现安全的超5G无线网络的势头来改变这一点。该团队正在联合学术界、工业界和政府的力量,重点是巩固其成员正在进行的5G安全相关研究工作。该项目还将通过为本科生和研究生的多元化团队创造涉及理论和实验的研究经验,为劳动力发展做出贡献。 拟议的研究有三个独特的属性,使零信任解决方案:(a)特别关注信号/波形水平和5G无线电接入网络(RAN)安全;(B)细粒度数据平面和控制平面威胁检测,跟踪和防御机制;(c)通过全栈,开放RAN/移动的核心测试平台进行集成和评估。DoD应用程序是提出解决方案的主要动机。为了缩小工作范围并使其更有基础,拟议的研究将在以下三个交织的方面进行组织:(i)在用户设备(UE),RAN,增强型数据全球演进(EDGE),回程和5G分组核心级别的威胁建模,以了解次优的5G网络;(ii)设计威胁检测、跟踪和保护算法/机制,有效修改5G RAN的信令和5G核心的软件功能/协议,以实现粒度访问控制和加密;以及(iii)在使用现有和新型可编程硬件的5G RAN、核心和互联网边缘的背景下,正式验证基于服务的架构的各种安全要求。该项目实现的可见性和可控性水平将使5G基于服务的架构能够快速适应,以安全和及时的方式为军事和其他关键服务让路-类似于汽车如何在高速公路上为救护车和消防车让路,该奖项反映了NSF的法定使命,并通过使用基金会的知识产权进行评估,优点和更广泛的影响审查标准。

项目成果

期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Dynamic and Robust Sensor Selection Strategies for Wireless Positioning With TOA/RSS Measurement
用于 TOA/RSS 测​​量无线定位的动态且鲁棒的传感器选择策略
  • DOI:
    10.1109/tvt.2023.3279833
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    6.8
  • 作者:
    Oh, Myeung Suk;Hosseinalipour, Seyyedali;Kim, Taejoon;Love, David J.;Krogmeier, James V.;Brinton, Christopher G.
  • 通讯作者:
    Brinton, Christopher G.
Learning-Based Adaptive IRS Control with Limited Feedback Codebooks
  • DOI:
    10.1109/twc.2022.3178055
  • 发表时间:
    2021-12
  • 期刊:
  • 影响因子:
    10.4
  • 作者:
    Junghoon Kim;Seyyedali Hosseinalipour;Andrew C. Marcum;Taejoon Kim;D. Love;Christopher G. Brinton
  • 通讯作者:
    Junghoon Kim;Seyyedali Hosseinalipour;Andrew C. Marcum;Taejoon Kim;D. Love;Christopher G. Brinton
Time-Varying Noise Perturbation and Power Control for Differential-Privacy-Preserving Wireless Federated Learning
Adaptive Frequency Hopping for 5G New Radio mMTC Security
用于 5G 新无线电 mMTC 安全的自适应跳频
  • DOI:
    10.1109/icit58465.2023.10143116
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Chan, Wai Ming;Kwon, Hyuck M.;Chou, Rémi A.;Love, David J.;Fahmy, Sonia;Hussain, Syed Rafiul;Kim, Sang Wu;Valk, Chris Vander;Brinton, Christopher G.;Marojevic, Vuk
  • 通讯作者:
    Marojevic, Vuk
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Taejoon Kim其他文献

A Hybrid Cache Architecture for Meeting Per-Tenant Performance Goals in a Private Cloud
用于满足私有云中每个租户性能目标的混合缓存架构
  • DOI:
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Taejoon Kim;Yu Gu;Jinoh Kim
  • 通讯作者:
    Jinoh Kim
Leveraging subspace information for low-rank matrix reconstruction
利用子空间信息进行低秩矩阵重建
  • DOI:
    10.1016/j.sigpro.2019.05.013
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Wei Zhang;Taejoon Kim;Guojun Xiong;S. Leung
  • 通讯作者:
    S. Leung
A Sequential Subspace Method for Millimeter Wave MIMO Channel Estimation
毫米波MIMO信道估计的顺序子空间方法
Design optimization of heat exchanger using deep reinforcement learning
  • DOI:
    10.1016/j.icheatmasstransfer.2024.107991
  • 发表时间:
    2024-12-01
  • 期刊:
  • 影响因子:
  • 作者:
    Geunhyeong Lee;Younghwan Joo;Sung-Uk Lee;Taejoon Kim;Yonggyun Yu;Hyun-Gil Kim
  • 通讯作者:
    Hyun-Gil Kim
Interference Analysis for Millimeter-Wave Networks With Geometry-Dependent First-Order Reflections
具有几何相关一阶反射的毫米波网络的干扰分析

Taejoon Kim的其他文献

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{{ truncateString('Taejoon Kim', 18)}}的其他基金

Collaborative Research: NSF-AoF: CNS Core: Small: Towards Scalable and Al-based Solutions for Beyond-5G Radio Access Networks
合作研究:NSF-AoF:CNS 核心:小型:面向超 5G 无线接入网络的可扩展和基于人工智能的解决方案
  • 批准号:
    2225577
  • 财政年份:
    2023
  • 资助金额:
    $ 75万
  • 项目类别:
    Standard Grant
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
  • 财政年份:
    2023
  • 资助金额:
    $ 75万
  • 项目类别:
    Cooperative Agreement
GOALI: CNS: Medium: Communication-Computation Co-Design for Rural Connectivtiy and Intelligence under Nonuniformity: Modeling, Analysis, and Implementation
目标:CNS:媒介:非均匀性下农村互联和智能的通信计算协同设计:建模、分析和实现
  • 批准号:
    2212565
  • 财政年份:
    2022
  • 资助金额:
    $ 75万
  • 项目类别:
    Standard Grant

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