Collaborative Research: SaTC: CORE: Small: UAV-NetSAFE.COM: UAV Network Security Assessment and Fidelity Enhancement through Cyber-Attack-Ready Optimized Machine-Learning Platforms

无人机（UAV）广泛用于民用、医疗保健和其他科学应用，例如气候监测、灾害和流行病管理、商品递送、搜索和救援行动以及太空探索。UAV-NetSAFE.COM项目旨在提高无人机网络的网络意识，开拓创新的安全解决方案，并通过直接减轻可能导致人员伤亡、敏感数据泄露和服务质量下降的网络攻击的严重性来服务于美国的国家利益。该合作项目通过研究用于预防、检测和缓解无人机网络攻击的多层安全框架来促进科学进步。此外，该项目还将影响其他具有高度社会利益的领域，如物联网和智能电网。它通过让学生参与教育和研究活动，如开发网络攻击模型，使用机器学习评估网络攻击，以及设计硬件和软件解决方案以实现可信赖的网络，支持网络安全，机器学习和无人机网络领域的更广泛教育。每年，该项目的成果将被整合到现有和新的课程中，并展示以吸引高中生攻读STEM学位。由女性领导PI从UND的带领下，这个合作项目的教育活动和跨学科的研究工作将受益于美国土著学生从北达科他州和经济弱势的少数民族和代表性不足的学生从芝加哥大都市和西北印第安纳州的状态。该项目由安全和值得信赖的网络空间计划和刺激竞争研究的既定计划（EPSCoR）共同资助。这个NSF SaTC合作项目的总体目标是调查网络攻击对无人机网络和先锋网络攻击准备平台的影响。从软件的角度来看，将推导出无人机网络的网络攻击模型，以促进无人机独特的数据集，这些数据集有助于采用定性风险调查和定量措施对无人机网络的网络攻击影响进行全面评估和事后评估。由此产生的数据集将通过采用先进的概率和统计机器学习算法，为无人机网络提供针对一系列网络攻击的攻击检测和决策协议。从硬件的角度来看，PI将探索软件定义的无线电设置，这些设置将射频波束成形电路模块与基于软件的定位和路径重新调度技术相结合，同时考虑尺寸和结构复杂性等实际限制。因此，该项目的主要贡献是开创了一个统一的框架，包括网络攻击评估，检测和软件和硬件设置的对策。PI将维护一个包罗万象的项目网站，这将有助于轻松地向工业和研究界传播网络攻击模型和对策方法的数据集，以确保拟议的框架促进无人机通信和网络安全。 该项目由安全和值得信赖的网络空间计划和刺激竞争研究的既定计划（EPSCoR）共同资助。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。

Unmanned aerial vehicles (UAVs) find widespread uses in civil, healthcare, and other scientific applications, such as climate monitoring, disaster and pandemic management, merchandise delivery, search and rescue operations, and space exploration. The project UAV-NetSAFE.COM promotes cyber-awareness of UAV networks, pioneers innovative security solutions, and serves the US national interest by directly mitigating the severity of cyber-attacks that could otherwise lead to human causalities, leakage of sensitive data, and degraded quality-of-service. This collaborative project promotes science advancement by investigating a multilayer security framework for the prevention, detection, and mitigation of UAV-oriented cyber-attacks. Also, this project will also impact other areas of high societal interest, such as Internet-of-Things and smart grids. It supports broader education in the areas of cyber-security, machine-learning, and UAV networks by engaging students in educational and research activities such as developing cyber-attack models, evaluating cyber-attacks using machine learning, and designing hardware as well as software solutions for trustworthy networking. Every year, the outcomes of this project will be integrated into existing and new curricula and showcased to attract high school students into STEM degrees. Led by a female lead PI from UND, this collaborative project's educational activities and interdisciplinary research endeavors will benefit Native American students from the state of North Dakota and economically disadvantaged minority and underrepresented students from Chicago metropolitan and NW Indiana. This project is jointly funded by Secure and Trustworthy Cyberspace Program and the Established Program to Stimulate Competitive Research (EPSCoR). The overarching goal of this NSF SaTC collaborative project is to investigate the impacts of cyber-attacks on UAV networks and pioneer cyber-attack-ready platforms. From a software perspective, UAV networks' cyber-attack models will be derived to facilitate UAV-distinctive datasets that aid in the comprehensive assessment and aftermath evaluation of cyber-attack impacts on UAV networks employing qualitative risk investigations and quantitative measures. The resulting datasets will be used to empower UAV networks with both attack detection and decision-making protocols for a range of cyber-attacks by adopting advanced probabilistic and statistical machine-learning algorithms. From a hardware perspective, the PIs will explore software-defined radio setups that intertwine radio frequency beamforming circuit modules with software-based localization and path rescheduling techniques while considering practical constraints such as size and structural complexity. Therefore, the project's key contribution is to pioneer a unified framework that entails cyber-attack evaluation, detection, and countermeasures of software and hardware setups. The PIs will maintain an all-inclusive project website that will help easily disseminate the datasets of cyber-attack models and countermeasure methods to industry and research community to ensure that the proposed framework promotes UAV communication and network security. This project is jointly funded by Secure and Trustworthy Cyberspace Program and the Established Program to Stimulate Competitive Research (EPSCoR).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.