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== Abstract ==
 
== Abstract ==
  
Part 2: CONTROL SYSTEMS SECURITY International audience Industrial control systems are cyber-physical systems that supervise and control physical processes in critical infrastructures such as electric grids, water and wastewater treatment plants, oil and natural gas pipelines, transportation systems and chemical plants and refineries. Leveraging the stable and persistent control flow communications patterns in industrial control systems, this chapter proposes an innovative control system fingerprinting methodology that analyzes industrial control protocols to capture normal behavior characteristics. The methodology can be used to identify specific physical processes and control system components in industrial facilities and detect abnormal behavior. An experimental testbed that incorporates real systems for the cyber domain and simulated systems for the physical domain is used to validate the methodology. The experimental results demonstrate that the fingerprinting methodology holds promise for detecting anomalies in industrial control systems and cyber-physical systems used in the critical infrastructure.
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Part 2: CONTROL SYSTEMS SECURITY; International audience; Industrial control systems are cyber-physical systems that supervise and control physical processes in critical infrastructures such as electric grids, water and wastewater treatment plants, oil and natural gas pipelines, transportation systems and chemical plants and refineries. Leveraging the stable and persistent control flow communications patterns in industrial control systems, this chapter proposes an innovative control system fingerprinting methodology that analyzes industrial control protocols to capture normal behavior characteristics. The methodology can be used to identify specific physical processes and control system components in industrial facilities and detect abnormal behavior. An experimental testbed that incorporates real systems for the cyber domain and simulated systems for the physical domain is used to validate the methodology. The experimental results demonstrate that the fingerprinting methodology holds promise for detecting anomalies in industrial control systems and cyber-physical systems used in the critical infrastructure.
  
 
Document type: Part of book or chapter of book
 
Document type: Part of book or chapter of book
  
 
== Full document ==
 
== Full document ==
<pdf>Media:Draft_Content_522503360-beopen491-6208-document.pdf</pdf>
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<pdf>Media:Peng_et_al_2015a-beopen2054-6776-document.pdf</pdf>
  
  
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The different versions of the original document can be found in:
 
The different versions of the original document can be found in:
  
* [https://hal.inria.fr/hal-01431014/file/978-3-319-26567-4_5_Chapter.pdf https://hal.inria.fr/hal-01431014/file/978-3-319-26567-4_5_Chapter.pdf] under the license cc-by
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* [https://hal.inria.fr/hal-01431014/file/978-3-319-26567-4_5_Chapter.pdf https://hal.inria.fr/hal-01431014/file/978-3-319-26567-4_5_Chapter.pdf] under the license https://creativecommons.org/licenses/by
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* [http://link.springer.com/content/pdf/10.1007/978-3-319-26567-4_5 http://link.springer.com/content/pdf/10.1007/978-3-319-26567-4_5],
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: [http://dx.doi.org/10.1007/978-3-319-26567-4_5 http://dx.doi.org/10.1007/978-3-319-26567-4_5] under the license cc-by
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* [https://hal.inria.fr/hal-01431014 https://hal.inria.fr/hal-01431014],
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: [https://hal.inria.fr/hal-01431014/document https://hal.inria.fr/hal-01431014/document],
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: [https://hal.inria.fr/hal-01431014/file/978-3-319-26567-4_5_Chapter.pdf https://hal.inria.fr/hal-01431014/file/978-3-319-26567-4_5_Chapter.pdf] under the license http://www.springer.com/tdm
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* [https://link.springer.com/chapter/10.1007%2F978-3-319-26567-4_5 https://link.springer.com/chapter/10.1007%2F978-3-319-26567-4_5],
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: [https://hal.inria.fr/hal-01431014/document https://hal.inria.fr/hal-01431014/document],
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: [https://hal.inria.fr/IFIP-AICT-466/hal-01431014 https://hal.inria.fr/IFIP-AICT-466/hal-01431014],
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: [https://doi.org/10.1007/978-3-319-26567-4_5 https://doi.org/10.1007/978-3-319-26567-4_5],
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: [https://dblp.uni-trier.de/db/conf/ifip11-10/iccip2015.html#PengXGCR15 https://dblp.uni-trier.de/db/conf/ifip11-10/iccip2015.html#PengXGCR15],
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: [https://rd.springer.com/chapter/10.1007/978-3-319-26567-4_5 https://rd.springer.com/chapter/10.1007/978-3-319-26567-4_5],
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: [https://academic.microsoft.com/#/detail/2267647354 https://academic.microsoft.com/#/detail/2267647354] under the license http://creativecommons.org/licenses/by/

Latest revision as of 20:04, 1 February 2021

Abstract

Part 2: CONTROL SYSTEMS SECURITY; International audience; Industrial control systems are cyber-physical systems that supervise and control physical processes in critical infrastructures such as electric grids, water and wastewater treatment plants, oil and natural gas pipelines, transportation systems and chemical plants and refineries. Leveraging the stable and persistent control flow communications patterns in industrial control systems, this chapter proposes an innovative control system fingerprinting methodology that analyzes industrial control protocols to capture normal behavior characteristics. The methodology can be used to identify specific physical processes and control system components in industrial facilities and detect abnormal behavior. An experimental testbed that incorporates real systems for the cyber domain and simulated systems for the physical domain is used to validate the methodology. The experimental results demonstrate that the fingerprinting methodology holds promise for detecting anomalies in industrial control systems and cyber-physical systems used in the critical infrastructure.

Document type: Part of book or chapter of book

Full document

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Original document

The different versions of the original document can be found in:

http://dx.doi.org/10.1007/978-3-319-26567-4_5 under the license cc-by
https://hal.inria.fr/hal-01431014/document,
https://hal.inria.fr/hal-01431014/file/978-3-319-26567-4_5_Chapter.pdf under the license http://www.springer.com/tdm
https://hal.inria.fr/hal-01431014/document,
https://hal.inria.fr/IFIP-AICT-466/hal-01431014,
https://doi.org/10.1007/978-3-319-26567-4_5,
https://dblp.uni-trier.de/db/conf/ifip11-10/iccip2015.html#PengXGCR15,
https://rd.springer.com/chapter/10.1007/978-3-319-26567-4_5,
https://academic.microsoft.com/#/detail/2267647354 under the license http://creativecommons.org/licenses/by/
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Published on 01/01/2015

Volume 2015, 2015
DOI: 10.1007/978-3-319-26567-4_5
Licence: CC BY-NC-SA license

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