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.

对各种关键任务的自治系统的兴趣，包括运输，搜救，监视，侦察，制图和消防，由于其大量安全性，机动性和环境福利而迅速增长。使用自动地面车辆有望每年预防超过900万事故和200万次伤害，节省70亿升的燃料，并挽救36,000多个燃料，同时将与事故相关的医疗费用降低了1900亿美元，但是，在美国，成功的任务执行和导航的成功任务依靠准确且可靠的位置，导航，导航和定位，服务（Pnt）和时间效果（Pnt和Pnt）。依赖于全球导航卫星系统（GNSS）的当前网络有弹性PNT解决方案采用了各种技术，例如惯性导航系统（INS），基于视觉的传感，地球轨道（LEO）卫星恒星或地面pseudo pseudo卫星的利用。但是，它们容易受到无意的干扰，多径问题，大气效应，部分错误，故意干扰或干扰以及欺骗。该职业项目可深入了解自治系统内置传感器（GNSS以及惯性和感知传感器）的融合和集成，用于在威胁不确定性和有争议的环境下进行网络弹性导航。该项目将调查与集成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水平网络攻击检测； （iv）在有争议的环境中安全自动导航；促进有关自动导航挑战的基本知识，而网络风险增加了。这项研究推动了在不断发展的网络威胁模式下，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使工程学生了解网络安全知识和技能，并通过基于游戏的学习（GBL）平台激发工程学和K-12学生来解决对未来网络安全劳动力的日益增长的需求在不断发展的攻击表面下，制定了强大，高效，灵活和可靠的定位和导航系统。研究计划的目的是对基于GNSS的高级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。该职业项目的中心假设是对定位和导航解决方案中动态威胁不确定性的系统考虑，旨在在威胁和有争议的环境下提供弹性的导航服务。 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有争议的环境。教育计划的目的是从整体的多学科角度为下一代工程师实施工程教育计划。教育目标包括（i）通过使未来的工程师参与跨学科研究和教育计划来装备； （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）让来自代表性不足群体的学生参与各种研究和教育努力； （iv）进行外展计划，以与更广泛的受众分享研究结果。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，被认为值得通过评估来获得支持。