课题基金 / 基金详情

RINGS: NextSec: Zero-Trust, Programmable and Verifiable Security Transformation for NextG

RINGS: NextSec: Zero-Trust, Programmable and Verifiable Security Transformation for NextG
RINGS:NextSec:NextG 的零信任、可编程和可验证安全转型
批准号:
2148374
负责人:
Guofei Gu
金额:
$100.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-05-01 至 2025-04-30

项目摘要

项目成果

Guofei Gu的其他基金

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中文摘要
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英文摘要
NextG network systems are expected to connect billions of heterogeneous Internet of Thing (IoT) devices along with billions of people, enable machine-to-machine communications, and provide low-latency computational and storage resources on-demand at the devices and in the cloud. In NextG, many services will run dynamically as lightweight functionalities close to users to support ultra-low latency when storing/processing extremely critical data, for example, from autonomous vehicles and tele-surgery. Historically, however, many of these services have been developed/deployed with no security in mind, or simply with security as a reactive add-on. This kind of security practice may beget life-threatening consequences for critical NextG applications/services. The project’s novelties are the introduction of a revolutionary capability for secure architecture for NextG and a system, NextSec, that enhances the security of NextG services. This project provides a solid foundation and collaborative community for future system and network security research. The project team incorporate insights and results from this work into relevant courses, recruit/educate underrepresented students in computing, and transfer the developed technology to industry. To address the challenges in the secure composition of microservices in the pervasive, distributed user-to-edge-to-cloud continuum of NextG network systems, this project has three research thrusts. The concept of security transformation is new for addressing the various security issues of microservices. The Programmable Security thrust provides new primitives for supporting a software-defined way of enforcing user-to-edge-to-cloud security. Finally, the extended Maximal Causality Reduction methods offer efficient, scalable verification of complex security properties across microservices. The framework has been evaluated on Texas A&M Commercial 4G/5G Advanced Wireless Application Research Environment (AWARE) testbed.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(1)
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会议论文
DOI: 10.1109/tifs.2023.3264152
发表时间: 2023
期刊: IEEE Transactions on Information Forensics and Security
影响因子: 6.8
作者: [Sungmin Hong;Lei Xu;Jianwei Huang;Hongda Li;Hongxin Hu;G. Gu]
通讯作者: Sungmin Hong;Lei Xu;Jianwei Huang;Hongda Li;Hongxin Hu;G. Gu
NSF Convergence Accelerator Track G: PETS: Programmable Zero-Trust Security for Operating Through 5G Infrastructure
Community-Building Workshop on Programmable System Security in a Software-Defined World
SaTC: CORE: Small: Adversarial Learning via Modeling Interpretation
EAGER: USBRCCR: Collaborative: Securing Networks in the Programmable Data Plane Era