NSF Convergence Accelerator Track G: Proactive End-to-End Zero Trust-Based Security Intelligence for Resilient Non-cooperative 5G Networks

NSF 融合加速器轨道 G：针对弹性非合作 5G 网络的主动式端到端基于零信任的安全情报

• 批准号: 2226232
• 负责人: Junaid Farooq
• 金额: $ 74.99万
• 依托单位: Regents of the University of Michigan - Dearborn
• 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
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2226232&HistoricalAwards=false
• 关键词: NSF; Convergence; Accelerator; Track; Proactive

Military and tactical units are required to operate in regions where a dedicated and trusted communications infrastructure may not be available. To communicate effectively, efficiently, and securely at all times, it is critical to have the ability of operating through untrusted indigenous infrastructure and at the same time, seamlessly and securely connect with devices on trusted networks. With the growing threat landscape and attack surfaces in 5G communication systems, a promising approach to tackle the security challenges is to adopt a holistic Zero Trust approach based on the principle of “never trust, always verify”. The goal of this project is to achieve trustworthy communications over untrusted and potentially compromised 5G networks by creating end-to-end security intelligence. The project team comprising of experts from academia, industry, and academic-industry partnerships, will accelerate the development of a software-based solution for automated and trustworthy network orchestration allowing military and critical infrastructure operators to securely communicate using commercial 5G networks. The project aims to develop capabilities that enable military and critical infrastructure personnel to securely communicate using both military and modern commercial 5G infrastructure anywhere in the world, without the risk of being breached or hacked. The developed tools will enhance the capabilities of tactical networks in enforcing Zero Trust and policy-based access management of tactical units. Furthermore, the convergence team will develop a cross-disciplinary curriculum for training and education of next-generation workforce on Zero Trust for 5G networks. Special emphasis will be placed on recruiting under-represented minority students in the research and development of secure 5G networks.This project will integrate cross-disciplinary expertise from trustworthy system design, machine learning/artificial intelligence, and 5G networks & edge computing to accelerate the automated creation of an overlay of proactive, end-to-end zero-trust security and resilience mechanism over the tactical 5G network cloud infrastructure. The convergence research is centered around three main thrusts. Thrust 1 will focus on the dynamic and proactive trust evaluation of tactical devices in the network. A distributed and autonomous approach will be used to collect information about device interactions, leverage triggers, and indicators to make quantitative trust assessments. Thrust 2 will use the trust information obtained in Thrust 1 to orchestrate network resources according to tactical mission scenarios and the requirements of different end-to-end paths. It will be achieved using a deep reinforcement learning approach by iteratively obtaining access permissions from a novel trust management engine and providing it with resource selection decisions. Thrust 3 will automate the access management system to proactively thwart unqualified access to critical resources and prevent lateral movement of attacks and malware. The tools developed as a result of this project will be oriented toward operational scenarios in tactical missions.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.

军事和战术部队需要在可能没有专用和可靠的通信基础设施的地区开展行动。为了始终有效、高效、安全地进行通信，必须能够通过不受信任的本地基础设施进行操作，同时与受信任网络上的设备无缝、安全地连接。随着5G通信系统中威胁和攻击面的不断增长，解决安全挑战的一种有希望的方法是采用基于“从不信任，始终验证”原则的整体零信任方法。该项目的目标是通过创建端到端安全情报，在不受信任和可能受损的5G网络上实现可信赖的通信。该项目团队由来自学术界、工业界和学术界的专家组成，将加速开发基于软件的解决方案，以实现自动化和可信赖的网络编排，使军事和关键基础设施运营商能够使用商用5G网络安全地进行通信。该项目旨在开发能力，使军事和关键基础设施人员能够在世界任何地方使用军事和现代商用5G基础设施进行安全通信，而不会有被入侵或黑客攻击的风险。开发的工具将增强战术网络在实施零信任和基于策略的战术单元访问管理方面的能力。此外，融合团队还将开发跨学科课程，用于培训和教育下一代5G网络零信任员工。该项目将特别强调招募代表性不足的少数民族学生参与安全5G网络的研究和开发。该项目将整合可信赖的系统设计，机器学习/人工智能和5G网络边缘计算等跨学科专业知识&，以加速自动创建覆盖主动，在战术5G网络云基础设施上实现端到端零信任安全和弹性机制。融合研究围绕三个主要方面展开。重点1将侧重于网络中战术设备的动态和主动信任评估。将使用分布式和自主方法收集有关设备交互、杠杆触发器和指标的信息，以进行定量信任评估。Thrust 2将使用Thrust 1中获得的信任信息，根据战术使命场景和不同端到端路径的要求编排网络资源。它将使用深度强化学习方法，通过迭代地从一个新的信任管理引擎获得访问权限并为其提供资源选择决策来实现。Thrust 3将使访问管理系统自动化，以主动阻止对关键资源的不合格访问，并防止攻击和恶意软件的横向移动。该项目开发的工具将面向战术任务中的作战场景。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。