CAREER: Cyber Resilient Navigation for Autonomous Systems under Threat Uncertainties and Contested Environments

职业：威胁不确定性和竞争环境下自主系统的网络弹性导航

• 批准号: 2340456
• 负责人: MIZANUR RAHMAN
• 金额: $ 53.6万
• 依托单位: University of Alabama Tuscaloosa
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-06-01 至 2029-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2340456&HistoricalAwards=false
• 关键词: CAREER; Cyber; Resilient; Navigation; Autonomous

The interest in autonomous systems for various critical missions, including transportation, search and rescue, surveillance, reconnaissance, mapping, and firefighting, is growing rapidly due to their significant safety, mobility, and environmental benefits. The use of autonomous ground vehicles promises to prevent more than 9 million accidents and 2 million injuries annually, conserve 7 billion liters of fuel and save more than 36,000 lives while reducing healthcare costs associated with accidents by $190 billion in the U.S. However, successful mission execution and navigation of autonomous systems rely on accurate and reliable positioning, navigation, and timing (PNT) services. Current cyber-resilient PNT solutions, which rely on global navigation satellite systems (GNSS), employ various techniques, such as inertial navigation systems (INS), vision-based sensing, the utilization of lower earth orbit (LEO) satellite constellations or terrestrial pseudo satellites. However, they are susceptible to unintentional interference, multipath issues, atmospheric effects, segment errors, intentional interference or jamming, and spoofing. This CAREER project generates in-depth insights into the fusion and integration of built-in sensors (GNSS along with inertial and perception sensors) of autonomous systems for cyber-resilient navigation under threat uncertainties and contested environments. This project will investigate four complex problems related to integrated navigation systems: (i) threat modeling and cyber risk assessment; (ii) self-learning-based cyber attack modeling; (iii) signal, sensor fusion and navigation solution levels cyber attack detection; and (iv) secure autonomous navigation in contested environment; to advance fundamental knowledge on autonomous navigation challenges aggravated by growing cyber risks. This research pushes the boundaries of the science of cyber-resilient navigation under evolving cyber threat patterns. In addition, education plan of this CAREER project addresses the increasing demand for a future cybersecurity workforce by exposing engineering students to cyber security knowledge and skills, and by inspiring engineering and K-12 students through game-based learning (GBL) platforms to think beyond the traditional cybersecurity solutions in addressing grand engineering challenges holistically.This CAREER project aims to advance the scientific discovery of fundamental dynamics in cyber threat uncertainties for autonomous navigation under evolving attack surfaces in formulating a robust, efficient, flexible, and reliable positioning and navigation system. The goal of the research plan is to pursue the scientific exploration of cyber threat uncertainties of advanced GNSS-based positioning and navigation systems, and secure navigation under threat and contested environments. The central hypothesis of this CAREER project is systematic considerations of the dynamic threat uncertainties in positioning and navigation solutions that aim to provide resilient navigation services under threats and contested environments. The research objectives of this CAREER project are to: (i) understand and assess cyber threat uncertainties of integrated positioning and navigation systems utilizing threat modeling approach, (ii) model self-learning based cyber-attacks to support the development of security-by-design navigation solutions, (iii) formulate a suite of cyber-attack detection algorithms under uncertainties, and (iv) develop a secure navigation solution through deep sensor fusion for a contested environment. The goal of the education plan is to implement an engineering education program for next-generation engineers from a holistic multidisciplinary perspective. The education objectives include (i) equip future engineers by engaging them in cross-disciplinary research and educational initiatives; (ii) create and implement a GBL platform for students in grades K-12 to enhance their understanding and interest in science, technology, engineering, and mathematics fields and related careers; (iii) involve students from under-represented groups in various research and educational endeavors; and (iv) conduct outreach programs to share the results of research with a broader audience.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.

由于自主系统具有显著的安全性、机动性和环境效益，人们对包括运输、搜救、监视、侦察、测绘和消防在内的各种关键任务的自主系统的兴趣正在迅速增长。自动地面车辆的使用有望每年防止900多万起事故和200万人受伤，节省70亿升燃料，拯救3.6万多人的生命，同时在美国减少与事故相关的医疗成本1900亿美元。然而，自动驾驶系统的成功执行任务和导航依赖于准确可靠的定位、导航和授时(PNT)服务。目前具有网络复原力的PNT解决方案依赖于全球导航卫星系统(GNSS)，采用了各种技术，例如惯性导航系统(INS)、基于视觉的传感、利用低地球轨道(LEO)卫星星座或地面伪卫星。但是，它们容易受到无意干扰、多路径问题、大气效应、网段错误、故意干扰或干扰以及欺骗的影响。这个职业项目对自主系统的内置传感器(GNSS以及惯性传感器和感知传感器)的融合和集成产生了深入的见解，以便在威胁、不确定因素和有争议的环境下进行网络弹性导航。该项目将研究与组合导航系统有关的四个复杂问题：(I)威胁建模和网络风险评估；(Ii)基于自学习的网络攻击建模；(Iii)信号、传感器融合和导航解决方案级别的网络攻击检测；以及(Iv)在竞争环境中的安全自主导航；增进关于自主导航挑战的基本知识，这些挑战因日益增长的网络风险而加剧。这项研究突破了在不断演变的网络威胁模式下进行网络弹性导航的科学界限。此外，这个职业项目的教育计划通过让工科学生接触网络安全知识和技能，并通过基于游戏的学习(GBL)平台激励工程学和K-12学生在整体应对重大工程挑战时超越传统的网络安全解决方案，来解决对未来网络安全劳动力日益增长的需求。这个职业项目旨在促进科学发现网络威胁不确定性中的基本动态，以便在不断变化的攻击面下自主导航，形成一个健壮、高效、灵活和可靠的定位和导航系统。该研究计划的目标是对先进的基于全球导航卫星系统的定位和导航系统的网络威胁不确定性进行科学探索，并在威胁和有争议的环境下进行安全导航。这个职业项目的中心假设是系统地考虑定位和导航解决方案中的动态威胁不确定性，旨在提供在威胁和竞争环境下的弹性导航服务。该职业项目的研究目标是：(I)利用威胁建模方法了解和评估组合定位和导航系统的网络威胁不确定性；(Ii)建立基于自学习的网络攻击模型，以支持设计安全的导航解决方案的开发；(Iii)制定一套不确定情况下的网络攻击检测算法；以及(Iv)通过深度传感器融合开发针对竞争环境的安全导航解决方案。该教育计划的目标是从整体、多学科的角度为下一代工程师实施工程教育计划。教育目标包括(I)通过让未来的工程师参与跨学科研究和教育活动来装备他们；(Ii)为K-12年级的学生创建和实施GBL平台，以提高他们对科学、技术、工程和数学领域及相关职业的理解和兴趣；(Iii)让代表不足的群体的学生参与各种研究和教育活动；以及(Iv)开展外联计划，与更广泛的受众分享研究成果。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。