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

基本信息

  • 批准号:
    2333980
  • 负责人:
  • 金额:
    $ 50万
  • 依托单位:
  • 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 2025-06-30
  • 项目状态:
    未结题

项目摘要

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.
由于新技术已集成以进行交互和控制物理系统,因此在网络物理系统(CPS)中出现了新的漏洞。除了软件和网络攻击外,传感器攻击是CPS中的至关重要的安全风险,在这种情况下,攻击者会改变感应信息,从而负面干扰物理系统。对恶意传感器信息作用可能会导致严重后果。尽管许多研究工作已致力于保护CPS免受传感器攻击的侵害,但仍未解决几个关键问题。首先,现有的攻击检测工作往往会同时最大程度地减少检测延迟和错误警报。但是,由于两个指标之间的固有权衡,这个目标并不总是可以实现的。其次,在攻击检测方面有很多工作,但是在检测攻击后该怎么做的关键问题仍然存在。重要的是,在发生无法弥补的后果之前,CPS应检测攻击并从攻击中恢复。 第三,检测与恢复之间的相互关系不足以引起注意:整合检测和恢复技术将导致对传感器攻击的更有效的防御能力。该项目旨在解决这些关键问题并开发新颖的检测和恢复技术。该项目旨在通过解决CP中的实时自适应攻击和恢复来及时,安全地防止传感器攻击。首先,该项目探讨了新的攻击检测技术,这些技术可以以数据驱动的方式动态平衡检测延迟与虚假警报率之间的权衡。 通过这种方式,检测器将以可预测的延迟进行攻击检测,并保持检测方法的可用性。其次,该项目采用了新的恢复技术,该技术在恢复截止日期之前将系统恢复到安全状态,同时最大程度地减少了系统执行的任务的退化。第三,该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,以显着改善对攻击的反应。具体的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和恢复协调技术。该技术将在多个CPS模拟器和自动驾驶汽车测试中进行实施和评估。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评估值得支持的。

项目成果

期刊论文数量(11)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Path Planning for UAVs Under GPS Permanent Faults
  • DOI:
    10.1145/3653074
  • 发表时间:
    2024-03
  • 期刊:
  • 影响因子:
    2.3
  • 作者:
    M. Sulieman;Mengyu Liu;M. C. Gursoy;Fanxin Kong
  • 通讯作者:
    M. Sulieman;Mengyu Liu;M. C. Gursoy;Fanxin Kong
Work in Progress: Emerging From Shadows: Optimal Hidden Actuator Attack to Cyber-Physical Systems
正在进行的工作:走出阴影:对网络物理系统的最佳隐藏执行器攻击
Fast Attack Recovery for Stochastic Cyber-Physical Systems
随机网络物理系统的快速攻击恢复
Catch You if Pay Attention: Temporal Sensor Attack Diagnosis Using Attention Mechanisms for Cyber-Physical Systems
  • DOI:
    10.1109/rtss59052.2023.00016
  • 发表时间:
    2023-12
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zifan Wang;Lin Zhang;Qinru Qiu;Fanxin Kong
  • 通讯作者:
    Zifan Wang;Lin Zhang;Qinru Qiu;Fanxin Kong
Poster Abstract: Assuring LLM-Enabled Cyber-Physical Systems
海报摘要:确保支持法学硕士的网络物理系统
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Fanxin Kong其他文献

Recovery-based Model Predictive Control for Cascade Mitigation under Cyber-Physical Attacks
基于恢复的模型预测控制,用于网络物理攻击下的级联缓解
Validation of estimating left ventricular ejection fraction by mitral annular displacement derived from speckle‐tracking echocardiography: A neglected method for evaluating left ventricular systolic function
通过斑点跟踪超声心动图衍生的二尖瓣环位移估计左心室射血分数的验证:一种被忽视的评估左心室收缩功能的方法
  • DOI:
    10.1002/jcu.22987
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0.9
  • 作者:
    Yonghuai Wang;Yan Zhang;Guangyuan Li;Fanxin Kong;Zhengyu Guan;Jun Yang;Chunyan Ma
  • 通讯作者:
    Chunyan Ma
CPSim: Simulation Toolbox for Security Problems in Cyber-Physical Systems
CPSim:网络物理系统安全问题的仿真工具箱
Applying Machine Learning in Designing Distributed Auction for Multi-agent Task Allocation with Budget Constraints
应用机器学习设计分布式拍卖以实现预算约束下的多代理任务分配
Incremental value of carotid elasticity modulus using shear wave elastography for identifying coronary artery disease in patients without carotid plaque
使用剪切波弹性成像技术评估颈动脉弹性模量的增量值,用于识别无颈动脉斑块患者的冠状动脉疾病
  • DOI:
    10.1097/hjh.0000000000002773
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    4.9
  • 作者:
    Yonghuai Wang;Cuiting Zhao;Pingping Meng;Yao Yu;Guangyuan Li;Fanxin Kong;Lixin Mu;Jun Yang;Chunyan Ma
  • 通讯作者:
    Chunyan Ma

Fanxin Kong的其他文献

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{{ truncateString('Fanxin Kong', 18)}}的其他基金

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
  • 财政年份:
    2022
  • 资助金额:
    $ 50万
  • 项目类别:
    Standard Grant
Collaborative Research: PPoSS: Planning:S3-IoT: Design and Deployment of Scalable, Secure, and Smart Mission-Critical IoT Systems
协作研究:PPoSS:规划:S3-IoT:可扩展、安全和智能任务关键型物联网系统的设计和部署
  • 批准号:
    2028740
  • 财政年份:
    2020
  • 资助金额:
    $ 50万
  • 项目类别:
    Standard Grant
EAGER: Techniques for Deploying Mission Critical IoT Applications
EAGER:部署关键任务物联网应用程序的技术
  • 批准号:
    1720579
  • 财政年份:
    2017
  • 资助金额:
    $ 50万
  • 项目类别:
    Standard Grant

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