CPS: Medium: Collaborative Research: Security vs. Privacy in Cyber-Physical Systems

CPS：媒介：协作研究：网络物理系统中的安全与隐私

• 批准号: 1837627
• 负责人: Alvaro Cardenas
• 金额: $ 63.48万
• 依托单位: University of Texas at Dallas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2019-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1837627&HistoricalAwards=false
• 关键词: CPS; Medium; Collaborative; Research; Security

This research examines the scientific foundations for modeling security and privacy trade-offs in cyber-physical systems, focusing in particular on settings where privacy-protection technologies might be abused by malicious parties to hide their attacks. The goal is to provide both security and privacy guarantees for a variety of cyber-physical systems including intelligent transportation systems, smart energy, and autonomous vehicles.Privacy and security in cyber-physical systems have been studied independently before, but often they have not been addressed jointly. This project will study privacy-protection mechanisms such as differential privacy, and explore how using such mechanisms can affect the state-of-art integrity and attack-detection mechanisms. The project will also develop novel defenses including: 1) Identifying fundamental trade-offs between privacy and security based theoretical analyses of privacy, control theory, and optimization methods, with applications such as traffic-density estimation and smart grids; 2) incorporating game-theoretic considerations in analyzing adversarial strategies; and 3) Proposing new privacy-preserving techniques applicable in cyber-physical systems and beyond.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.

这项研究探讨了在网络物理系统中建模安全和隐私权衡的科学基础，特别关注隐私保护技术可能被恶意方滥用以隐藏其攻击的环境。其目标是为各种网络物理系统提供安全和隐私保障，包括智能交通系统，智能能源和自动驾驶汽车。网络物理系统中的隐私和安全以前曾被独立研究，但通常没有被联合解决。该项目将研究隐私保护机制，如差异隐私，并探讨使用这些机制如何影响最先进的完整性和攻击检测机制。该项目还将开发新的防御措施，包括：1）基于隐私、控制理论和优化方法的理论分析，确定隐私和安全之间的基本权衡，并应用于交通密度估计和智能电网等领域; 2）在分析对抗策略时考虑博弈论因素; 3）提出新的隐私保护技术，适用于网络，该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准。

项目成果

Private Anomaly Detection in Linear Controllers: Garbled Circuits vs. Homomorphic Encryption

线性控制器中的私有异常检测：乱码电路与同态加密

• 发表时间: 2022
• 期刊: 61st IEEE Conference on Decision and Control
• 作者: Alexandru, A.;Burbano, L.;Cardenas, A.;Celiktug, M.;Gomez, J.;Katz, J.;Kantarcioglu, M.
• 通讯作者: Kantarcioglu, M.