Collaborative Research: SaTC: CORE: Small: Towards Robust, Scalable, and Resilient Radio Fingerprinting

协作研究：SaTC：核心：小型：迈向稳健、可扩展和有弹性的无线电指纹识别

• 批准号: 2225161
• 负责人: Nirnimesh Ghose
• 金额: $ 30万
• 依托单位: University of Nebraska-Lincoln
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-15 至 2026-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2225161&HistoricalAwards=false
• 关键词: Collaborative; Research; SaTC; CORE; Small

Radio fingerprinting can distinguish wireless devices using radio frequency signals, as unique device hardware imperfections are carried in such signals. Radio fingerprinting is a physical-layer authentication technique and plays a critical role in identifying individual devices (e.g., IoT devices) and mission-critical targets (e.g., Unmanned Aerial Vehicles). This project develops new methods to promote the robustness, scalability, and resilience of radio fingerprinting by synergizing deep learning and signal processing. This project addresses three research questions, specifically (1) how to improve the robustness of radio fingerprinting against temporal variations of wireless channels; (2) how to mitigate nonlinear receiver hardware imperfections; and (3) how to improve the resilience of radio fingerprinting against white-box attackers. The research outcomes of this project will be disseminated through publications and new course modules and projects. These will promote cybersecurity workforce development as well as broaden the participation of students from underrepresented groups in computing.This project is jointly funded by the Secure and Trustworthy Cyberspace (SaTC) 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.

无线电指纹可以使用射频信号来区分无线设备，因为在此类信号中携带独特的设备硬件缺陷。无线电指纹识别是一种物理层的身份验证技术，在识别单个设备（例如IoT设备）和关键任务目标（例如无人驾驶飞机）方面起着至关重要的作用。该项目开发了新方法，以通过协同深度学习和信号处理来促进无线电指纹识别的鲁棒性，可扩展性和弹性。该项目解决了三个研究问题，特别是（1）如何改善无线通道时间变化的无线电指纹的鲁棒性； （2）如何减轻非线性接收器硬件缺陷； （3）如何提高针对白盒攻击者的无线电指纹的弹性。该项目的研究成果将通过出版物，新课程模块和项目传播。这些将促进网络安全劳动力的发展，并扩大了代表性不足的团体参与计算的学生的参与。该项目由安全且可信赖的网络空间（SATC）计划共同资助，以及既定的计划，以及启发竞争性研究（EPSCOR）的既定计划（EPSCOR）。这些奖项反映了NSF的范围，以众多的范围进行了跨国公司的范围，其范围是众所周知的范围。 标准。