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.

这项研究研究了在网络物理系统中建模安全和隐私权衡取舍的科学基础，尤其是针对隐私保护技术可能被恶意党滥用以掩盖其攻击的环境。目的是为各种网络物理系统提供安全性和隐私保证，包括智能运输系统，智能能源和自动驾驶汽车。以前已经独立研究了网络物理系统的私有性和安全性，但通常没有共同解决它们。该项目将研究诸如差异隐私之类的隐私保护机制，并探讨使用此类机制如何影响最新的完整性和攻击检测机制。该项目还将开发新的防御能力，包括：1）基于隐私，控制理论和优化方法的隐私和安全性之间的基本权衡，以及交通密度估计和智能电网等应用； 2）将游戏理论考虑在分析对抗策略中； 3）提出了适用于网络物理系统及以后的新的保留隐私技术。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评估标准来通过评估来获得支持的。

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.