课题基金 / 基金详情

Encrypted control for privacy-preserving and secure cyber-physical systems

Encrypted control for privacy-preserving and secure cyber-physical systems
隐私保护和安全网络物理系统的加密控制
批准号:
1912702
负责人:
Yongqiang Wang
金额:
$38.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-15 至 2024-08-31

项目摘要

项目成果

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中文摘要
翻译
在云计算和无线通信的推动下,许多控制系统越来越多地与传感、通信和计算设备集成,从而产生所谓的网络物理系统(CPS)。CPS的典型例子包括关键的水、天然气和电力基础设施、群机器人和车辆排。这些控制系统通常通过通信网络关闭反馈控制回路,由于(共享)通信网络的脆弱性,导致严重的隐私和安全挑战。事实上,对安全,特别是隐私的关注已经促使各种立法政策和建议,用于许多隐私和安全关键CPS,如智能电网和智能交通系统。例如,美国国家公路交通安全管理局要求在实施车对车通信时必须解决隐私问题,必须采取隐私措施以防止个人在位置上被跟踪。尽管控制界和计算机科学界的研究人员已经提出了若干技术解决方案来增强CPS的隐私性和安全性,但是现有的方法未能将控制理论方法与传统的信息技术解决方案(如加密)联合收割机组合和协同。,大大限制了保护CPS隐私和安全的整体可实现的强度和范围。这项建议旨在提供加密的通过无缝集成控制和加密,实现CPS隐私和安全保护的控制方法。这种集成创造了巨大的协同效应,并实现了新的功能:它不仅可以在没有任何数据聚合器或第三方的情况下实现分散的隐私和安全保护,还可以避免损害准确性,这是基于差异隐私的隐私保护方法的典型问题。此外,无缝集成也保证了低计算复杂度。该项目将:i)发展加密控制架构及相应的云端控制理论,以保障隐私,即使在加密控制架构下出现陈述错误,亦能确保隐私的稳定性; ii)在加密控制架构下,发展新的验证机制,以对抗对通信链路及云端等共享计算平台的完整性攻击; iii)将加密控制扩展到完全分散的多代理设置,而无需任何数据聚合器或第三方;以及iv)使用多机器人平台系统地验证该方法。拟议的研究将为智能电网和联网汽车等通用CPS提供隐私和安全保护,其中隐私和安全至关重要。预计它还将影响许多其他关键基础设施,例如水和废水系统,在这些系统中,对通信网络的控制正在成为常态。该项目将大大丰富现有的研究生/本科生课程的密码学和控制,其中PI定期教。它还将通过利用现有NSF RTG赠款下的预定培训活动以及通过克莱姆森WISE下对少数民族中学女生的持续推广活动,直接解决少数民族和妇女在科学和工程领域代表性不足的问题(妇女在科学和工程)该奖项反映了NSF的法定使命,并已被认为是值得通过评估使用基金会的智力价值和更广泛的支持影响审查标准。
英文摘要
Driven by advances in cloud computing and wireless communications, many control systems are increasingly integrated with sensing, communication, and computing devices, leading to the so-called cyber-physical systems (CPS). Typical examples of CPS include critical water, gas, and power infrastructures, swarm robotics, and vehicle platoons. Those control systems usually have their feedback control loops closed via communication networks, leading to critical privacy and security challenges due to the vulnerability of (shared) communication networks. In fact, concerns on security and particularly privacy have spurred various legislative polices and recommendations for many privacy-and-security critical CPS like smart grids and intelligent transportation systems. For example, the National Highway Traffic Safety Administration has required that privacy issues must be addressed when implementing vehicle-to-vehicle communications, and privacy measures must be undertaken to prevent individuals from being tracked in location. Although researchers in the control community and the computer science community have proposed several technological solutions to enhance the privacy and security of CPS, existing approaches fail to combine and synergize control-theoretical approaches with conventional information technology solutions like encryption, which significantly restricts the overall achievable strength and scope in protecting the privacy and security of CPS.This proposal seeks to provide an encrypted control approach for CPS privacy-and-security protection by seamlessly integrating control and encryption. The integration creates tremendous synergy and enables new capabilities: not only does it enable decentralized privacy-and-security protection without any data aggregator or third-party, it also avoids compromising accuracy, a typical problem with differential-privacy based privacy-protection approaches. Furthermore, the seamless integration guarantees low computational complexity as well. The project will: i) develop an encrypted control framework and corresponding theories for cloud-based control to protect privacy with guaranteed stability despite encryption-induced representation errors; ii) under the encrypted control framework, develop new verification mechanisms to combat integrity attacks on both communication links and shared computing platforms such as the cloud; iii) extend the encrypted control to completely decentralized multi-agent settings without any data aggregator or third-party; and iv) systematically validate the approach using a multi-robot platform. The proposed research will provide privacy-and-security protection for general CPS such as smart grids and connected vehicles, in which privacy and security are crucial. It is also expected to impact many other critical infrastructures such as water and wastewater systems where control over communication networks is becoming the norm. The project will significantly enrich existing graduate/undergraduate courses in cryptography and control, which the PIs regularly teach. It will also directly address the underrepresentation of ethnic groups and women in science and engineering through leveraging scheduled training activities under an existing NSF RTG grant as well as through ongoing outreach activities to minority middle-school girls under the Clemson WISE (Women in Science and Engineering) program.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.
期刊论文(14)
专著(0)
科研奖励(0)
会议论文
DOI: 10.23919/ccc58697.2023.10240327
发表时间: 2023-07
期刊: 2023 42nd Chinese Control Conference (CCC)
影响因子: --
作者: [Yongqiang Wang]
通讯作者: Yongqiang Wang
DOI: 10.1109/cdc49753.2023.10383541
发表时间: 2022-11
期刊: 2023 62nd IEEE Conference on Decision and Control (CDC)
影响因子: --
作者: [Yongqiang Wang]
通讯作者: Yongqiang Wang
DOI: 10.1109/tac.2024.3351068
发表时间: 2024
期刊: IEEE Transactions on Automatic Control
影响因子: 6.8
作者: [Wang, Yongqiang, Nedić, Angelia]
通讯作者: Nedić, Angelia
DOI: 10.1109/cdc49753.2023.10383285
发表时间: 2023-12
期刊: 2023 62nd IEEE Conference on Decision and Control (CDC)
影响因子: --
作者: [Yongqiang Wang;A. Nedić]
通讯作者: Yongqiang Wang;A. Nedić
共 12 条
    CIF: Small: Ensuring Accuracy in Differentially Private Decentralized Optimization
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    • 项目类别:
      Standard Grant
    • 资助金额:
      $59.99万
    • 财政年份:
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    FRR: Collaborative Research: Collaborative Learning for Multi-robot Systems with Model-enabled Privacy Protection and Safety Supervision
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      Standard Grant
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      $38.76万
    • 财政年份:
      2022
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      Yongqiang Wang
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    CIF: Small: Deep Stochasticity for Private Collaborative Deep Learning
    • 批准号:
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    • 财政年份:
      2022
    • 负责人:
      Yongqiang Wang
    • 依托单位:
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    • 项目类别:
      Continuing Grant
    • 资助金额:
      $50.0万
    • 财政年份:
      2021
    • 负责人:
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    • 依托单位:
    国内基金
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    • 项目类别:
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      LY21E080004
    • 项目类别:
      省市级项目
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      --
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    • 项目类别:
      青年科学基金项目
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    • 批准年份:
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    • 负责人:
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