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Collaborative Research: CPS: Medium: Sensor Attack Detection and Recovery in Cyber-Physical Systems

Collaborative Research: CPS: Medium: Sensor Attack Detection and Recovery in Cyber-Physical Systems
合作研究:CPS:中:网络物理系统中的传感器攻击检测和恢复
批准号:
2143256
负责人:
Fanxin Kong
金额:
$50.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-07-15 至 2023-07-31

项目摘要

项目成果

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中文摘要
翻译
随着新技术被集成到交互和控制物理系统中,网络物理系统(CPS)中出现了新的漏洞。除了软件和网络攻击之外,传感器攻击是CPS中的一个重要安全风险,攻击者会改变传感信息以对物理系统产生负面干扰。对恶意传感器信息采取行动可能会导致严重后果。虽然许多研究都致力于保护CPS免受传感器攻击,但仍有几个关键问题尚未解决。首先,现有的攻击检测工作倾向于同时最小化检测延迟和虚警;然而,由于两个度量标准之间的内在权衡,这个目标并不总是可以实现的。其次,在攻击检测方面已经做了很多工作,但一个关键问题仍然存在,即在检测到攻击后该怎么做。重要的是,CPS应该检测攻击并在无法挽回的后果发生之前从攻击中恢复过来。第三,检测和恢复之间的相互关系没有得到足够的重视:将检测和恢复技术结合起来可以更有效地防御传感器攻击。本项目旨在解决这些关键问题,并开发新的检测和恢复技术。该项目旨在通过解决CPS中的实时自适应攻击检测和恢复,实现对传感器攻击的及时和安全防御。首先,本项目探索了新的攻击检测技术,该技术可以以数据驱动的方式动态平衡检测延迟和误报率之间的权衡。这样,检测器将以可预测的延迟提供攻击检测,并保持检测方法的可用性。其次,该项目追求新的恢复技术,使系统在恢复截止日期之前恢复到安全状态,同时最大限度地减少系统对正在执行的任务的退化。第三,本项目研究了以协调的方式解决攻击检测和恢复的有效技术,以显着提高对攻击的响应。具体研究任务包括开发实时自适应传感器攻击检测技术、实时攻击恢复技术以及攻击检测与恢复协调技术。开发的技术将在多个CPS模拟器和自动驾驶汽车试验台上实施和评估。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
New vulnerabilities arise in Cyber-Physical Systems (CPS) as new technologies are integrated to interact and control physical systems. In addition to software and network attacks, sensor attacks are a crucial security risk in CPS, where an attacker alters sensing information to negatively interfere with the physical system. Acting on malicious sensor information can cause serious consequences. While many research efforts have been devoted to protecting CPS from sensor attacks, several critical problems remain unresolved. First, existing attack detection works tend to minimize the detection delay and false alarms at the same time; this goal, however, is not always achievable due to the inherent trade-off between the two metrics. Second, there has been much work on attack detection, yet a key question remains concerning what to do after detecting an attack. Importantly, a CPS should detect an attack and recover from the attack before irreparable consequences occur. Third, the interrelation between detection and recovery has met with insufficient attention: Integrating detection and recovery techniques would result in more effective defenses against sensor attacks.This project aims to address these key problems and develop novel detection and recovery techniques. The project aims to achieve timely and safe defense against sensor attacks by addressing real-time adaptive-attack detection and recovery in CPS. First, this project explores new attack detection techniques that can dynamically balance the trade-off between the detection delay and the false-alarm rate in a data-driven fashion. In this way, the detector will deliver attack detection with predictable delay and maintain the usability of the detection approach. Second, this project pursues new recovery techniques that bring the system back to a safe state before a recovery deadline while minimizing the degradation to the mission being executed by the system. Third, this project investigates efficient techniques that address the attack detection and recovery in a coordinated fashion to significantly improve response to attacks. Specific research tasks include the development of real-time adaptive sensor attack detection techniques, real-time attack recovery techniques, and attack detection and recovery coordination techniques. The developed techniques will be implemented and evaluated on multiple CPS simulators and an autonomous vehicle testbed.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(6)
专著(0)
科研奖励(0)
会议论文
Fail-Safe: Securing Cyber-Physical Systems against Hidden Sensor Attacks
故障安全:保护网络物理系统免受隐藏传感器攻击
DOI: 10.1109/rtss55097.2022.00029
发表时间: 2022
期刊: 2022 IEEE Real-Time Systems Symposium (RTSS
影响因子: --
作者: [Liu, Mengyu, Zhang, Lin, Lu, Pengyuan, Sridhar, Kaustubh, Kong, Fanxin, Sokolsky, Oleg, Lee, Insup]
通讯作者: Lee, Insup
Real-Time Data-Predictive Attack-Recovery for Complex Cyber-Physical Systems
复杂网络物理系统的实时数据预测攻击恢复
DOI: --
发表时间: 2023
期刊: 29th IEEE Real-Time and Embedded Technology and Applications Symposium
影响因子: --
作者: [Zhang, Lin, Sridhar, Kaustubh, Liu, Mengyu, Lu, Pengyuan, Chen, Xin, Kong, Fanxin, Sokolsky, Oleg, Lee, Insup]
通讯作者: Lee, Insup
DOI: 10.1109/isorc58943.2023.00018
发表时间: 2023-05
期刊: 2023 IEEE 26th International Symposium on Real-Time Distributed Computing (ISORC)
影响因子: --
作者: [Francis Akowuah;Kenneth Fletcher;Fanxin Kong]
通讯作者: Francis Akowuah;Kenneth Fletcher;Fanxin Kong
Optimal Checkpointing Strategy for Real-time Systems with Both Logical and Timing Correctness
具有逻辑和时序正确性的实时系统的最佳检查点策略
DOI: 10.1145/3603172
发表时间: 2023
期刊: ACM Transactions on Embedded Computing Systems
影响因子: 2
作者: [Zhang, Lin, Wang, Zifan, Kong, Fanxin]
通讯作者: Kong, Fanxin
共 6 条
    Collaborative Research: CPS: Medium: Sensor Attack Detection and Recovery in Cyber-Physical Systems
    • 批准号:
      2333980
    • 项目类别:
      Standard Grant
    • 资助金额:
      $50.0万
    • 财政年份:
      2023
    • 负责人:
      Fanxin Kong
    • 依托单位:
    Collaborative Research: PPoSS: Planning:S3-IoT: Design and Deployment of Scalable, Secure, and Smart Mission-Critical IoT Systems
    • 批准号:
      2028740
    • 项目类别:
      Standard Grant
    • 资助金额:
      $5.0万
    • 财政年份:
      2020
    • 负责人:
      Fanxin Kong
    • 依托单位:
    EAGER: Techniques for Deploying Mission Critical IoT Applications
    • 批准号:
      1720579
    • 项目类别:
      Standard Grant
    • 资助金额:
      $28.57万
    • 财政年份:
      2017
    • 负责人:
      Fanxin Kong
    • 依托单位:
    国内基金
    海外基金
    Research on Quantum Field Theory without a Lagrangian Description
    • 批准号:
      24ZR1403900
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2024
    • 负责人:
      SATOSHI NAWATA
    • 依托单位:
    Cell Research
    Cell Research
    Cell Research (细胞研究)