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.

由于其显着的安全性、机动性和环境效益，人们对用于各种关键任务（包括运输、搜索和救援、监视、侦察、测绘和消防）的自主系统的兴趣正在迅速增长。在美国，使用自动地面车辆有望每年防止超过 900 万起事故和 200 万人受伤，节省 70 亿升燃料，挽救超过 36,000 人的生命，同时将与事故相关的医疗费用减少 1,900 亿美元。然而，自动系统的成功任务执行和导航依赖于准确可靠的定位、导航和授时 (PNT) 服务。当前的网络弹性 PNT 解决方案依赖于全球导航卫星系统 (GNSS)，采用各种技术，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。然而，它们容易受到无意干扰、多径问题、大气影响、分段错误、故意干扰或干扰以及欺骗的影响。该职业项目深入了解自主系统内置传感器（GNSS 以及惯性和感知传感器）的融合和集成，以在威胁不确定性和有争议的环境下实现网络弹性导航。该项目将研究与组合导航系统相关的四个复杂问题：（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； (iv) 在有争议的环境中确保自主导航的安全；提高有关因日益增长的网络风险而加剧的自主导航挑战的基础知识。这项研究在不断发展的网络威胁模式下突破了网络弹性导航科学的界限。此外，该职业项目的教育计划通过向工科学生展示网络安全知识和技能，并通过基于游戏的学习（GBL）平台启发工程和 K-12 学生超越传统的网络安全解决方案来思考，全面应对重大工程挑战，从而满足对未来网络安全劳动力日益增长的需求。该职业项目旨在推进对自主导航网络威胁不确定性的基本动态的科学发现 应对不断变化的攻击面，制定稳健、高效、灵活、可靠的定位导航系统。该研究计划的目标是对基于 GNSS 的先进定位和导航系统的网络威胁不确定性进行科学探索，并在威胁和竞争环境下实现安全导航。该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，旨在在威胁和竞争环境下提供弹性导航服务。该职业项目的研究目标是：（i）利用威胁建模方法理解和评估集成定位和导航系统的网络威胁不确定性，（ii）基于自学习的网络攻击建模以支持安全设计导航解决方案的开发，（iii）制定一套不确定性下的网络攻击检测算法，以及（iv）通过深度传感器融合开发安全导航解决方案 有争议的环境。该教育计划的目标是从整体多学科的角度实施下一代工程师的工程教育计划。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 年级的学生创建并实施 GBL 平台，以增强他们对科学、技术、工程和数学领域及相关职业的理解和兴趣； (iii) 让代表性不足群体的学生参与各种研究和教育活动； (iv) 开展外展计划，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价值和更广泛的影响审查标准进行评估，被认为值得支持。