Resilient Monitoring Systems: Architecture, Design, and Application to Boiler/Turbine Plant

Garcia, Humberto E.; Lin, Wen-Chiao; Meerkov, Semyon M.; Ravichandran, Maruthi T.

doi:10.1109/TCYB.2014.2316003

Title: Resilient Monitoring Systems: Architecture, Design, and Application to Boiler/Turbine Plant

Abstract

Resilient monitoring systems, considered in this paper, are sensor networks that degrade gracefully under malicious attacks on their sensors, causing them to project misleading information. The goal of this work is to design, analyze, and evaluate the performance of a resilient monitoring system intended to monitor plant conditions (normal or anomalous). The architecture developed consists of four layers: data quality assessment, process variable assessment, plant condition assessment, and sensor network adaptation. Each of these layers is analyzed by either analytical or numerical tools. The performance of the overall system is evaluated using a simplified boiler/turbine plant. The measure of resiliency is quantified using Kullback-Leibler divergence, and is shown to be sufficiently high in all scenarios considered.

Authors:: Garcia, Humberto E.; Lin, Wen-Chiao; Meerkov, Semyon M.; Ravichandran, Maruthi T.

Publication Date:: Sat Nov 01 00:00:00 EDT 2014

Research Org.:: Idaho National Lab. (INL), Idaho Falls, ID (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1177641

Grant/Contract Number:: AC07-05ID14517

Resource Type:: Accepted Manuscript

Journal Name:: IEEE Transactions on Cybernetics

Additional Journal Information:: Journal Volume: 44; Journal Issue: 11; Journal ID: ISSN 2168-2267

Publisher:: IEEE

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING; Industrial Plants; TURBINES; BOILERS; MONITORING; Adaptive Systems; Reliability; DESIGN; Systems Analysis; Evaluation; cyber-physical attacks; cyber/physical condition assessments; graceful degradation; rational controllers; resiliency; resilient monitoring; Resilient systems

Citation Formats


                    Garcia, Humberto E., Lin, Wen-Chiao, Meerkov, Semyon M., and Ravichandran, Maruthi T. Resilient Monitoring Systems: Architecture, Design, and Application to Boiler/Turbine Plant.  United States: N. p., 2014. 
Web.  doi:10.1109/TCYB.2014.2316003.

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                    Garcia, Humberto E., Lin, Wen-Chiao, Meerkov, Semyon M., & Ravichandran, Maruthi T. Resilient Monitoring Systems: Architecture, Design, and Application to Boiler/Turbine Plant.  United States.  https://doi.org/10.1109/TCYB.2014.2316003

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                    Garcia, Humberto E., Lin, Wen-Chiao, Meerkov, Semyon M., and Ravichandran, Maruthi T. Sat .  
"Resilient Monitoring Systems: Architecture, Design, and Application to Boiler/Turbine Plant".  United States.  https://doi.org/10.1109/TCYB.2014.2316003.  https://www.osti.gov/servlets/purl/1177641.

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@article{osti_1177641,

  title        = {Resilient Monitoring Systems: Architecture, Design, and Application to Boiler/Turbine Plant},

  author       = {Garcia, Humberto E. and Lin, Wen-Chiao and Meerkov, Semyon M. and Ravichandran, Maruthi T.},

  abstractNote = {Resilient monitoring systems, considered in this paper, are sensor networks that degrade gracefully under malicious attacks on their sensors, causing them to project misleading information. The goal of this work is to design, analyze, and evaluate the performance of a resilient monitoring system intended to monitor plant conditions (normal or anomalous). The architecture developed consists of four layers: data quality assessment, process variable assessment, plant condition assessment, and sensor network adaptation. Each of these layers is analyzed by either analytical or numerical tools. The performance of the overall system is evaluated using a simplified boiler/turbine plant. The measure of resiliency is quantified using Kullback-Leibler divergence, and is shown to be sufficiently high in all scenarios considered.},

  doi          = {10.1109/TCYB.2014.2316003},

  journal      = {IEEE Transactions on Cybernetics},

  number       = 11,

  volume       = 44,

  place        = {United States},

  year         = {Sat Nov 01 00:00:00 EDT 2014},

  month        = {Sat Nov 01 00:00:00 EDT 2014}

}

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Title: Resilient Monitoring Systems: Architecture, Design, and Application to Boiler/Turbine Plant

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