CAREER: Understanding the Integrated Cyber-Physical Resilience of Continuous Critical Manufacturing
职业:了解连续关键制造的集成网络物理弹性
基本信息
- 批准号:2338968
- 负责人:
- 金额:$ 55.55万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2024
- 资助国家:美国
- 起止时间:2024-05-01 至 2029-04-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Industrial internet-of-things (IIoT) technologies spark growing interest in manufacturing security and resilience. However, current solutions lack a holistic understanding of cyber-physical resilience in complex systems, failing to connect IIoT network vulnerabilities with dynamic manufacturing processes for effective detection and control. To address these gaps, this Faculty Early Career Development (CAREER) project aims to develop novel methodologies that integrate modeling, detection, and control measures for understanding the cyber-physical resilience of continuous critical manufacturing systems. This study will work to eliminate barriers to the development of new policies, regulations, and standards for IIoT applications in manufacturing. In collaboration with industry stakeholders, this project promises long-term benefits by extending its methods and tools to other critical infrastructures, thereby enhancing national cyber-physical resilience. Meanwhile, the education and outreach activities in this project foster sustained awareness of cyber-physical resilience among both future and current manufacturing professionals. Introducing new courses and training materials enhances students' exposure to advanced manufacturing technologies and improves their data science and cybersecurity skills. K-12 outreach initiatives boost understanding of IIoT and cyber-physical resilience, promoting manufacturing careers. A specially designed training software addresses the need for intuitive cybersecurity training in engineering language. These endeavors align with the National Strategy for Advanced Manufacturing by contributing to the goal of ensuring national security.This study addresses critical challenges in continuous manufacturing systems' cyber-physical resilience. The research objectives include (1) Development of Generalizable Tools: The project aims to build generalizable tools for cyber-physical resilience quantification. By creating stochastic models that integrate cyber connectivity and system dynamics of heterogeneous components, a novel quantification metric will be established. This metric considers both IIoT network features and manufacturing system dynamics through stochastic optimization, revealing system-level risks induced by IIoT connectivity. (2) Rethinking Anomaly Detection: The project will rethink cyber-physical resilience-driven anomaly detection by incorporating system-wide resilience quantification into process-based anomaly detection algorithms. This involves designing novel semi-supervised learning algorithms that incorporate resilience, with a focus on understanding the theories governing detection accuracy and resilience enhancement in high-dimensional data-driven anomaly detection. (3) Collaborative Learning-Based Resilient Control Strategies: The study aims to create collaborative learning-based resilient control strategies. Leveraging reinforcement learning and system connectivity, these strategies enhance a system's adaptability to cyberattacks. This involves exploring the under-explored area of vertical federated reinforcement learning and generating new knowledge regarding the trade-off between the control performance of individual machines and the system's adaptability to adversaries.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.
工业物联网(IIoT)技术激发了人们对制造安全性和弹性的兴趣。然而,目前的解决方案缺乏对复杂系统中网络物理弹性的整体理解,未能将IIoT网络漏洞与动态制造过程联系起来,以进行有效的检测和控制。为了解决这些差距,这个教师早期职业发展(CAREER)项目旨在开发新的方法,集成建模,检测和控制措施,以了解连续关键制造系统的网络物理弹性。这项研究将努力消除制造业中IIoT应用的新政策、法规和标准制定的障碍。通过与行业利益攸关方合作,该项目有望通过将其方法和工具扩展到其他重要基础设施,从而提高国家网络物理复原力,带来长期效益。与此同时,该项目的教育和外展活动促进了未来和当前制造业专业人员对网络物理复原力的持续认识。引入新的课程和培训材料可以提高学生对先进制造技术的接触,并提高他们的数据科学和网络安全技能。K-12外展计划促进了对IIoT和网络物理弹性的理解,促进了制造业的职业发展。专门设计的培训软件满足了工程语言中直观的网络安全培训需求。这些努力与国家先进制造战略保持一致,有助于实现确保国家安全的目标。本研究解决了连续制造系统的网络物理弹性方面的关键挑战。研究目标包括:(1)开发可推广的工具:本项目旨在构建可推广的网络物理弹性量化工具。通过创建集成网络连接和异构组件的系统动力学的随机模型,将建立一种新的量化度量。该指标通过随机优化考虑了IIoT网络特征和制造系统动态,揭示了IIoT连接性引起的系统级风险。(2)重新思考异常检测:该项目将通过将全系统范围的弹性量化纳入基于流程的异常检测算法,重新思考网络物理一致性驱动的异常检测。这涉及到设计新的半监督学习算法,其中包括弹性,重点是理解在高维数据驱动的异常检测中管理检测准确性和弹性增强的理论。(3)基于协作学习的弹性控制策略:本研究旨在创建基于协作学习的弹性控制策略。利用强化学习和系统连接,这些策略增强了系统对网络攻击的适应性。这涉及探索垂直联邦强化学习的未开发领域,并产生关于单个机器的控制性能和系统对对手的适应性之间的权衡的新知识。该奖项反映了NSF的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估而被认为值得支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Dan Li其他文献
Periods and Motives: Applications in Mathematical Physics
周期和动机:数学物理中的应用
- DOI:
- 发表时间:
2012 - 期刊:
- 影响因子:0
- 作者:
Dan Li - 通讯作者:
Dan Li
Assessment of Scientific Reasoning: the Effects of Task Context, Data, and Design on Student Reasoning in Control of Variables.
科学推理评估:任务背景、数据和设计对学生控制变量推理的影响。
- DOI:
- 发表时间:
2016 - 期刊:
- 影响因子:3.7
- 作者:
Shao;Jing Han;K. Koenig;Amy Raplinger;Yuan Pi;Dan Li;Hua Xiao;Zhao Fu;Lei Bao - 通讯作者:
Lei Bao
The Analysis and Improvement of KEELOQ Algorithm
KEELOQ算法的分析与改进
- DOI:
10.17706/ijcee.2017.9.2.439-444 - 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
Dan Li;Wenjun Xiao;Ziyi You;Yi Wang - 通讯作者:
Yi Wang
Sensitivities of seven algal species to triclosan, fuoxetine and their mixtures
七种藻类对三氯生、氟西汀及其混合物的敏感性
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:4.6
- 作者:
Ran Bi;Xiangfeng Zeng;Lei Mu;Liping Hou;Wenhua Liu;Ping Li;Hongxing Chen;Dan Li;Agnes Bouchez;Jiaxi Tang;Lingtian Xie - 通讯作者:
Lingtian Xie
PAMAM Dendrimer-Coordinated Copper(II) Complexes as a Theranostic Nanoplatform for Radiotherapy-Enhanced MR Imaging and Chemotherapy of Tumors and Tumor Metastasis
PAMAM 树枝状聚合物配位铜 (II) 配合物作为治疗诊断纳米平台,用于肿瘤和肿瘤转移的放射治疗增强 MR 成像和化疗
- DOI:
- 发表时间:
2019 - 期刊:
- 影响因子:10.8
- 作者:
Yu Fan;Jiulong Zhang;Menghan Shi;Dan Li;Chunhua Lu;Xueyan Cao;Chen Peng;Serge Mignani;Jean-Pierre Majoral;Xiangyang Shi - 通讯作者:
Xiangyang Shi
Dan Li的其他文献
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{{ truncateString('Dan Li', 18)}}的其他基金
Collaborative Research: The Role of Coherent Structures in Scalar Transport over Heterogeneous Landscapes
合作研究:相干结构在异质景观标量传输中的作用
- 批准号:
1853354 - 财政年份:2019
- 资助金额:
$ 55.55万 - 项目类别:
Continuing Grant
Collaborative Research: PREEVENTS Track 2: Land-atmosphere feedbacks over urban terrain under heat waves
合作研究:预防事件轨道 2:热浪下城市地形的陆地大气反馈
- 批准号:
1854706 - 财政年份:2019
- 资助金额:
$ 55.55万 - 项目类别:
Continuing Grant
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