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CPS: TTP Option: Synergy: A Verifiable Framework for Cyber- Physical Attacks and Countermeasures in a Resilient Electric Power Grid

CPS: TTP Option: Synergy: A Verifiable Framework for Cyber- Physical Attacks and Countermeasures in a Resilient Electric Power Grid
CPS:TTP 选项:协同:弹性电网中网络物理攻击和对策的可验证框架
批准号:
1449080
负责人:
Lalitha Sankar
金额:
$140.0万
依托单位:
依托单位国家:
美国
项目类别:
Cooperative Agreement
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-03-01 至 2020-02-29

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中文摘要
翻译
电网,一个网络物理系统(CPS),面临着令人震惊的高风险,来自网络攻击的灾难性损害。然而,模拟网络攻击、评估后果和制定适当的对策需要一个详细、现实和易处理的电力CPS操作模型。主要障碍是无法获得电网几十年来一直依赖的复杂遗留专有系统的模型。该项目旨在通过开发攻击验证(可验证)软件框架来克服这些挑战,该软件框架将充分详细地捕获电力系统的运行。网络威胁将使用这一框架,通过合理的理论方法和可通过独特的过渡到实践(TTP)选项访问的开源商业模拟引擎相结合来验证。这项研究集中在四个基本和相关的方面:(I)识别具有可量化物理后果的网络攻击类别并开发基于检测的对策;(Ii)识别针对分布式电网操作的通信攻击并开发信息共享对策;(Iii)开发一个可验证的软件框架,以模拟电网与推力(I)和(Ii)协同的时空操作;(Ii)验证攻击模型、评估对策并开发新的弹性协议;以及(Iv)与IncSys和PowerData的行业领先专家合作的TTP方案,以开发商业级开源电源仿真软件包,以集成和测试推进器(I)至(Iii)的攻击和对策,并为北美电气可靠性委员会(NERC)认证开发劳动力培训课程。这项研究还包括通过亚利桑那州科学实验室项目与K-12学生接触。
英文摘要
The electric power grid, a cyber-physical system (CPS), faces an alarmingly high risk of catastrophic damage from cyber-attacks. However, modeling cyber-attacks, evaluating consequences, and developing appropriate countermeasures require a detailed, realistic, and tractable model of electric power CPS operations. The primary barrier is the lack of access to models for the complex legacy proprietary systems upon which the electric power grid has relied for decades. This project aims to overcome these challenges with the development of an attack-verifying (verifiable) software framework that will capture the electric power system operations in adequate detail. Cyber threats will be verified using this framework through a combination of sound theoretical methods and an open-source commercial simulation engine accessible via a unique transition to practice (TTP) option. This research focuses on four fundamental and related thrusts: (i) identifying classes of cyber-attacks with quantifiable physical consequences and developing detection-based countermeasures; (ii) identifying communication attacks on distributed grid operations and developing information-sharing countermeasures; (iii) developing a verifiable software framework that models the spatio-temporal operations of the electric grid in tandem with thrusts (i) and (ii) to verify attack models, evaluate countermeasures, and develop new resiliency protocols; and (iv) a TTP option, in collaboration with industry-leading experts from IncSys and PowerData, to develop commercial grade open source power simulation software packages to integrate and test the attacks and countermeasures of Thrusts (i) through (iii) as well as develop workforce training curriculum for North American Electric Reliability Council (NERC) certification. This research also includes engagement with K-12 students via the Arizona Science Laboratory program.
期刊论文(3)
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会议论文
DOI: 10.1049/iet-stg.2020.0030
发表时间: 2020-03
期刊: ArXiv
影响因子: --
作者: [Zhigang Chu;O. Kosut;L. Sankar]
通讯作者: Zhigang Chu;O. Kosut;L. Sankar
DOI: 10.1109/smartgridcomm.2019.8909739
发表时间: 2019-05
期刊: 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
影响因子: --
作者: [Zhigang Chu;Andrea Pinceti;R. Biswas;O. Kosut;A. Pal;L. Sankar]
通讯作者: Zhigang Chu;Andrea Pinceti;R. Biswas;O. Kosut;A. Pal;L. Sankar
Data-Driven Generation of Synthetic Load Datasets Preserving Spatio-Temporal Features
数据驱动的合成负载数据集生成保留时空特征
DOI: 10.1109/pesgm40551.2019.8973532
发表时间: 2019
期刊: 2019 IEEE Power & Energy Society General Meeting (PESGM
影响因子: --
作者: [Pinceti, Andrea, Kosut, Oliver, Sankar, Lalitha]
通讯作者: Sankar, Lalitha
Exploiting Physical and Dynamical Structures for Real-time Inference in Electric Power Systems
  • 批准号:
    2246658
  • 项目类别:
    Standard Grant
  • 资助金额:
    $36.0万
  • 财政年份:
    2023
  • 负责人:
    Lalitha Sankar
  • 依托单位:
Collaborative Research: SCH: Fair Federated Representation Learning for Breast Cancer Risk Scoring
  • 批准号:
    2205080
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.0万
  • 财政年份:
    2022
  • 负责人:
    Lalitha Sankar
  • 依托单位:
Unifying Information- and Optimization-Theoretic Approaches for Modeling and Training Generative Adversarial Networks
  • 批准号:
    2134256
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $110.0万
  • 财政年份:
    2021
  • 负责人:
    Lalitha Sankar
  • 依托单位:
RAPID: SaTC: FACT: Federated Analytics based Contact Tracing for COVID-19
  • 批准号:
    2031799
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.0万
  • 财政年份:
    2020
  • 负责人:
    Lalitha Sankar
  • 依托单位:
国内基金
海外基金
RNA结合蛋白TTP在阿尔茨海默病中的作用机制研究
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2023
  • 负责人:
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TTP和XPO4蛋白介导lncRNA转运在子宫颈鳞状细胞癌中功能及机制的研究
  • 批准号:
    --
  • 项目类别:
    面上项目
  • 资助金额:
    54万元
  • 批准年份:
    2022
  • 负责人:
    陈亮
  • 依托单位:
平滑肌中TTP在血压调控中的作用及机制研究
  • 批准号:
    --
  • 项目类别:
    面上项目
  • 资助金额:
    52万元
  • 批准年份:
    2022
  • 负责人:
    张文程
  • 依托单位:
TTP-KDM3A/CYP19A1调控滋养层细胞分化和侵袭的机制研究
  • 批准号:
    82171669
  • 项目类别:
    面上项目
  • 资助金额:
    54万元
  • 批准年份:
    2021
  • 负责人:
    林羿
  • 依托单位: