An Industrial Control System Cybersecurity Performance Testbed

Candell, Richard; Zimmerman, Timothy; Stouffer, Keith

doi:10.6028/nist.ir.8089

Cited by 38 publications

(30 citation statements)

References 3 publications

(7 reference statements)

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“…As a consequence, much of the research that is relevant is instead conducted either in toy scenarios or on simulated systems. The Tennessee-Eastman chemical process, a real-world industrial chemical manufacturing process, with available Matlab/Simulink code is one of the go-to simulator for security work in the field, and NIST have produced a cybersecurity performance testbed based on this model [106]. There has been a number of testbeds that have been proposed for industrial control systems research [107], however, most of these testbeds fail to accurately represent the real system under study.…”

Section: Future Research Directionsmentioning

confidence: 99%

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Security of smart manufacturing systems

Tuptuk

Hailes

2018

Journal of Manufacturing Systems

338

138

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A B S T R A C TA revolution in manufacturing systems is underway: substantial recent investment has been directed towards the development of smart manufacturing systems that are able to respond in real time to changes in customer demands, as well as the conditions in the supply chain and in the factory itself. Smart manufacturing is a key component of the broader thrust towards Industry 4.0, and relies on the creation of a bridge between digital and physical environments through Internet of Things (IoT) technologies, coupled with enhancements to those digital environments through greater use of cloud systems, data analytics and machine learning. Whilst these individual technologies have been in development for some time, their integration with industrial systems leads to new challenges as well as potential benefits. In this paper, we explore the challenges faced by those wishing to secure smart manufacturing systems. Lessons from history suggest that where an attempt has been made to retrofit security on systems for which the primary driver was the development of functionality, there are inevitable and costly breaches. Indeed, today's manufacturing systems have started to experience this over the past few years; however, the integration of complex smart manufacturing technologies massively increases the scope for attack from adversaries aiming at industrial espionage and sabotage. The potential outcome of these attacks ranges from economic damage and lost production, through injury and loss of life, to catastrophic nation-wide effects. In this paper, we discuss the security of existing industrial and manufacturing systems, existing vulnerabilities, potential future cyber-attacks, the weaknesses of existing measures, the levels of awareness and preparedness for future security challenges, and why security must play a key role underpinning the development of future smart manufacturing systems.

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Section: Future Research Directionsmentioning

confidence: 99%

“…Journal of Manufacturing Systems 47 (2018) [93][94][95][96][97][98][99][100][101][102][103][104][105][106] example, the data held in data historians' and engineers' workstations could be altered, or the network data packets could be changed causing, significant damage to the operation of the plant.…”

Section: N Tuptuk S Hailesmentioning

confidence: 99%

Security of smart manufacturing systems

Tuptuk

Hailes

2018

Journal of Manufacturing Systems

338

138

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“…From a more control-theoretic standpoint, Candell et al report in [43] a testbed to analyze the performance of security mechanisms for cyber-physical systems. The work reports as well discussions from control and security practitioners.…”

Section: Implementation Of Experimental Testbedsmentioning

confidence: 99%

On the use of watermark-based schemes to detect cyber-physical attacks

Rubio‐Hernan

Cicco

García-Alfaro

2017

EURASIP J. on Info. Security

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We address security issues in cyber-physical systems (CPSs). We focus on the detection of attacks against cyber-physical systems. Attacks against these systems shall be handled both in terms of safety and security. Networked-control technologies imposed by industrial standards already cover the safety dimension. However, from a security standpoint, using only cyber information to analyze the security of a cyber-physical system is not enough, since the physical malicious actions that can threaten the correct behavior of the systems are ignored. For this reason, the systems have to be protected from threats to their cyber and physical layers. Some authors have handled replay and integrity attacks using, for example, physical attestation to validate the cyber process and to detect the attacks, or watermark-based detectors which uses also physical parameters to ensure the cyber layers. We reexamine the effectiveness of a stationary watermark-based detector. We show that this approach only detects adversaries that do not attempt to get any knowledge about the system dynamics. We analyze the detection ratio of the original design under the presence of new adversaries that are able to infer the system dynamics and are able to evade the detector with high frequency. We propose a new detection scheme which employs several non-stationary watermarks. We validate the detection efficiency of the new strategy via numeric simulations and via running experiments on a laboratory testbed. Results show that the proposed strategy is able to detect adversaries using non-parametric methods, but it is not equally effective against adversaries using parametric identification methods.

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“…The National Institute of Standards and Technology has constructed a testbed to measure the performance impact induced by cybersecurity technologies on Industrial Control Systems (ICS) [1]. The testbed allows researchers to emulate real-world industrial manufacturing processes and their control systems without the need to replicate an entire factory environment or its machinery.…”

Section: Introductionmentioning

confidence: 99%

Metrics and key performance indicators for robotic cybersecurity performance analysis

Zimmerman¹

2017

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An Industrial Control System Cybersecurity Performance Testbed

Cited by 38 publications

References 3 publications

Security of smart manufacturing systems

Security of smart manufacturing systems

On the use of watermark-based schemes to detect cyber-physical attacks

Metrics and key performance indicators for robotic cybersecurity performance analysis

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