Key performance indicators for process control system cybersecurity performance analysis

Tang, CheeYee

doi:10.6028/nist.ir.8188

Cited by 14 publications

(8 citation statements)

References 3 publications

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“…The presented use-case utilizes a variation of the IPCS of this testbed as set up by National Institute of Standards and Technology (NIST) to define an example where an adverse event can be detected through CE [43]. This version of the model assumes a decentralized process controller for control loop continuous operation.…”

Section: Use-case Scenariomentioning

confidence: 99%

“…Composition measurements can be omitted to avoid a multi-rate sampling problem [44]. The original publications that introduced the TEC testbed list the plant's process nominal input demands as ranges of input values for equipment protection [42], [43]. Variable value ranges are restricted by existing operating constrains of the TEC's chemical process, within finite domains of operation.…”

Section: A Step-by-step Description On a Real-world Environmentmentioning

confidence: 99%

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Chaos Engineering for Enhanced Resilience of Cyber-Physical Systems

Konstantinou¹,

Stergiopoulos²,

Parvania³

et al. 2021

Preprint

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Cyber-physical systems (CPS) incorporate the complex and large-scale engineered systems behind critical infrastructure operations, such as water distribution networks, energy delivery systems, healthcare services, manufacturing systems, and transportation networks. Industrial CPS in particular need to simultaneously satisfy requirements of available, secure, safe and reliable system operation against diverse threats, in an adaptive and sustainable way. These adverse events can be of accidental or malicious nature and may include natural disasters, hardware or software faults, cyberattacks, or even infrastructure design and implementation faults. They may drastically affect the results of CPS algorithms and mechanisms, and subsequently the operations of industrial control systems (ICS) deployed in those critical infrastructures. Such a demanding combination of properties and threats calls for resilience-enhancement methodologies and techniques, working in real-time operation. However, the analysis of CPS resilience is a difficult task as it involves evaluation of various interdependent layers with heterogeneous computing equipment, physical components, network technologies, and data analytics. In this paper, we apply the principles of chaos engineering (CE) to industrial CPS, in order to demonstrate the benefits of such practices on system resilience. The systemic uncertainty of adverse events can be tamed by applying runtime CE-based analyses to CPS in production, in order to predict environment changes and thus apply mitigation measures limiting the range and severity of the event, and minimizing its blast radius.

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Section: Use-case Scenariomentioning

confidence: 99%

Section: A Step-by-step Description On a Real-world Environmentmentioning

confidence: 99%

Chaos Engineering for Enhanced Resilience of Cyber-Physical Systems

Konstantinou¹,

Stergiopoulos²,

Parvania³

et al. 2021

Preprint

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“…Continuous manufacturing usually implies a 24/7 (24 hours a day, seven days a week) operation with infrequent maintenance shutdowns and is contrasted with batch manufacturing. Examples of continuous manufacturing systems are chemical production, oil refining, natural-gas processing, and wastewater treatment [9]. An architecture of the PCS network is depicted in Figure 3-3.…”

Section: Process Control Systemmentioning

confidence: 99%

Securing manufacturing industrial control systems:

McCarthy¹,

Powell²,

Stouffer³

et al. 2020

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Certain commercial entities, equipment, or materials may be identified in this document in order to describe an experimental procedure or concept adequately. Such identification is not intended to imply recommendation or endorsement by NIST, nor is it intended to imply that the entities, materials, or equipment are necessarily the best available for the purpose.There may be references in this publication to other publications currently under development by NIST in accordance with its assigned statutory responsibilities. The information in this publication, including concepts and methodologies, may be used by federal agencies even before the completion of such companion publications. Thus, until each publication is completed, current requirements, guidelines, and procedures, where they exist, remain operative. For planning and transition purposes, federal agencies may wish to closely follow the development of these new publications by NIST.Organizations are encouraged to review all draft publications during public comment periods and provide feedback to NIST. Many NIST cybersecurity publications, other than the ones noted above, are available at https://csrc.nist.gov/publications.

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“…The Manufacturing Profile implementation will be performed on the Cybersecurity for Smart Manufacturing Systems testbed [2], located at the NIST campus in Gaithersburg, Maryland. The testbed contains two manufacturing systems: the Collaborative Robotics System (CRS) [3], and the Process Control System (PCS) [4]. The CRS is a discrete manufacturing process, while the PCS is a continuous manufacturing process.…”

Section: Cybersecurity For Smart Manufacturing Systems Testbedmentioning

confidence: 99%

Manufacturing profile implementation methodology for a robotic workcell

Zimmerman¹

2019

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The National Institute of Standards and Technology has constructed a testbed to measure the performance impact of cybersecurity technologies on Industrial Control Systems (ICS). The testbed was chosen to support the implementation of the Cybersecurity Framework Manufacturing Profile: a voluntary, risk-based approach for managing cybersecurity activities and reducing cyber risk to manufacturing systems. This report focuses on the Collaborative Robotics System, one of the two manufacturing systems within the testbed. A methodology for implementation of technical solutions to meet the Profile language is described, as well as a comprehensive review of the testbed measurement systems, and the comparative analysis procedures used for identifying performance impacts. Finally, an example comparative analysis is performed and the characterization of the workcell is discussed.

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Key performance indicators for process control system cybersecurity performance analysis

Cited by 14 publications

References 3 publications

Chaos Engineering for Enhanced Resilience of Cyber-Physical Systems

Chaos Engineering for Enhanced Resilience of Cyber-Physical Systems

Securing manufacturing industrial control systems:

Manufacturing profile implementation methodology for a robotic workcell

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