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Collaborative Research: CNS Core: Small: Closing the Theory-Practice Gap in Understanding and Combating Epidemic Spreading on Resource-Constrained Large-Scale Networks

Collaborative Research: CNS Core: Small: Closing the Theory-Practice Gap in Understanding and Combating Epidemic Spreading on Resource-Constrained Large-Scale Networks
合作研究:CNS核心:小型:缩小理解和抗击资源有限的大规模网络上的流行病传播的理论与实践差距
批准号:
2007423
负责人:
Do Young Eun
金额:
$25.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-10-01 至 2024-09-30

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中文摘要
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英文摘要
There has been an explosive growth in the number of Internet-connected devices. The end-device users have also built a stack of rich and complex networks, derived from their social, personal and work groups. The prolific connections to end-devices and users, however, can be exploited as devastating vehicles for malware and worm attacks. Since exploiting the network connectivity lies at the heart of malware distribution, it becomes crucial to understand how the underlying network structure affects the malware propagation. Despite abundant literature on epidemic modeling and analysis, there is still a huge gap between theory and practice. This project aims to bridge the gap to better understand and combat epidemic spreading on large-scale networks with realistic cost constraints.This collaborative project brings together investigators from Florida Institute of Technology and North Carolina State University to investigate the following inter-related research thrusts. It will (1) develop a theoretical framework to fully characterize the transient dynamics of epidemic spreading on a general graph (as opposed to a complete graph) to estimate and predict the likelihood of each node being infected for the future time, (2) develop a suite of readily usable algorithms to mitigate the spread of an epidemic to the extent possible under realistic constraints, and (3) develop a set of algorithms for efficient estimation and inference of network and epidemic parameters from incomplete and noisy data of epidemic cascades. This project could potentially have a high impact on a vast range of multi-disciplinary areas and applications where the study of epidemics has been necessary and crucial, including epidemiology, percolation in physics and chemistry, rumor spreading, information cascades, viral marketing, and spread of misinformation and fake news. In addition, this project will integrate research findings into education by curriculum development, involve diverse undergraduate and graduate students, especially women and students of underrepresented groups, and have them trained to thrive and contribute to the society in industrial and academic settings after graduation.All products developed during the course of this project will be publicly available and hosted at https://sites.google.com/view/nsf-cns-eun-lee-epidemic for at least three years after the closing of the project.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(5)
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科研奖励(0)
会议论文
DOI: 10.1109/tnet.2022.3213015
发表时间: 2022-10
期刊: IEEE/ACM Transactions on Networking
影响因子: --
作者: [Vishwaraj Doshi;Shailaja Mallick;Do Young Eun]
通讯作者: Vishwaraj Doshi;Shailaja Mallick;Do Young Eun
Controlling Epidemic Spread Under Immunization Delay Constraints
在免疫延迟限制下控制疫情蔓延
DOI: --
发表时间: 2023
期刊: IFIP Networking 2023
影响因子: --
作者: [Li, Shiju, Huang, Xin, Lee, Chul-Ho Lee, Eun, Do Young]
通讯作者: Eun, Do Young
DOI: 10.1109/tnse.2021.3108075
发表时间: 2021-10
期刊: IEEE Transactions on Network Science and Engineering
影响因子: 6.6
作者: [Srinjoy Chattopadhyay;H. Dai;Do Young Eun]
通讯作者: Srinjoy Chattopadhyay;H. Dai;Do Young Eun
DOI: 10.1109/cdc51059.2022.9992411
发表时间: 2022-09
期刊: 2022 IEEE 61st Conference on Decision and Control (CDC)
影响因子: --
作者: [Vishwaraj Doshi;Jie Hu;Do Young Eun]
通讯作者: Vishwaraj Doshi;Jie Hu;Do Young Eun
III: Small: Collaborative Research: Cost-Efficient Sampling and Estimation from Large-Scale Networks
  • 批准号:
    1910749
  • 项目类别:
    Standard Grant
  • 资助金额:
    $25.0万
  • 财政年份:
    2019
  • 负责人:
    Do Young Eun
  • 依托单位:
NeTS: Small: Distributed and Efficient Randomized Algorithms for Large Networks
  • 批准号:
    1217341
  • 项目类别:
    Standard Grant
  • 资助金额:
    $36.69万
  • 财政年份:
    2012
  • 负责人:
    Do Young Eun
  • 依托单位:
TF-SING: A Theoretical Foundation of Spatio-Temporal Mobility Modeling and Induced Link-Level Dynamics
  • 批准号:
    0830680
  • 项目类别:
    Standard Grant
  • 资助金额:
    $27.0万
  • 财政年份:
    2008
  • 负责人:
    Do Young Eun
  • 依托单位:
NEDG: Efficient Design and Control of Heterogeneous Mobile Networks: Beyond Poisson Regime
  • 批准号:
    0831825
  • 项目类别:
    Standard Grant
  • 资助金额:
    $29.99万
  • 财政年份:
    2008
  • 负责人:
    Do Young Eun
  • 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)