Collaborative Research: SaTC: CORE: Small: Secure and Privacy-Preserving Dynamic Spectrum Access

协作研究：SaTC：核心：小型：安全且保护隐私的动态频谱访问

• 批准号: 2325564
• 负责人: Rui Zhang
• 金额: $ 20万
• 依托单位: University of Delaware
• 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: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2325564&HistoricalAwards=false
• 关键词: Collaborative; Research; SaTC; CORE; Small

Dynamic spectrum sharing (DSS) is a crucial solution to the ever-increasing wireless spectrum shortage. DSS systems typically use an automated frequency coordinator called a Spectrum Access System (SAS), which uses both dedicated and crowdsourced spectrum sensors to enable on-demand, cost-effective spectrum sensing with extraordinary geographic coverage and granularity. Crowdsourcing-assisted DSS systems have long faced security and privacy concerns. The project’s novelties are the development, concept prototying, and evaluation of TrustSAS, an innovative AI/ML-powered trustworthy SAS that utilizes both dedicated and crowdsourced spectrum sensors to ensure comprehensive and efficient spectrum utilization while maintaining strong security and privacy. The project's broader significance and importance are the exploration of the latest advances in AI/ML technologies to enable trustworthy DSS and the contribution to the advancement of scientific research in AI/ML-driven wireless and mobile security systems. The proposed research includes three integrated thrusts. Thrust 1 develops VeriSS, a pioneer framework for verifiable spectrum sensing that employs graphical neural networks to analyze spectrum-sensing data and evaluate their trustworthiness even in the presence of potentially compromised spectrum sensors. Thrust 2 investigates TrustSML, a novel framework that builds upon VeriSS to achieve fast, accurate, and trustworthy localization of multiple simultaneous spectrum misusers. Thrust 3 studies PriCCS, a novel spatial crowdsourcing framework that enables the TrustSAS system operator to perform cost-effective and accurate spectrum-sensing task assignment while providing strong location privacy guarantees to participating crowd workers. The project's deliverables, including tutorials, talks, publications, and open-source toolkits, will be made publicly available online. The proposed research will be integrated into curriculum development, enhancing undergraduate research experiences and fostering broad participation in computing.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.

动态频谱共享（DSS）是无线频谱短缺的关键解决方案。 DSS系统通常使用称为Spectrum访问系统（SAS）的自动频率协调器，该系统使用专用和众包光谱传感器来实现具有非凡的地理覆盖范围和颗粒状的按需，具有成本效益的光谱灵敏度。众包辅助的DSS系统长期以来面临安全性和隐私问题。该项目的新颖性是Trustsas的开发，概念原型和评估，这是一种创新的AI/ML驱动的可信赖的SA，它利用专用和众包的窥镜传感器，以确保在维持强大的安全性和特权的同时，以确保全面有效的投机利用。该项目更广泛的意义和重要性是探索AI/ML技术的最新进展，以实现可信赖的DSS以及对AI/ML驱动的无线和移动安全系统中科学研究的进步的贡献。拟议的研究包括三个综合推力。推力1开发Veriss，这是一种可验证的光谱灵敏度的先锋框架，该范围使用图形神经网络来分析频谱感密度数据并评估其可信度，即使在存在潜在损害的光谱传感器的情况下也是如此。 Thrust 2调查了Trustsml，这是一个新颖的框架，它建立在Veriss上，以实现多个简单频谱的sixusers的快速，准确和值得信赖的本地化。推力3研究PRICC是一种新型的空间众包框架，使TrustSAS系统操作员能够执行具有成本效益，准确的光谱感应任务任务，同时提供强大的位置隐私保证为参与人群的工作人员提供了保证。该项目的可交付成果，包括教程，演讲，出版物和开源工具包，将在线公开提供。拟议的研究将纳入课程开发，增强本科研究经验并促进广泛参与计算。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响来评估标准。

项目成果

Locally Differentially Private and Fair Key-Value Aggregation

• DOI: 10.1145/3628797.3628807
• 发表时间: 2023-12
• 期刊: Proceedings of the 12th International Symposium on Information and Communication Technology
• 作者: Yukun Dong;Zhengwu Lu;Rui Zhang