Risk Assessment For Industrial Control Systems Quantifying Availability Using Mean Failure Cost (MFC)

Chen, Qian; Abercrombie, Robert K.; Sheldon, Frederick T.

doi:10.1515/jaiscr-2015-0029

Cited by 19 publications

(8 citation statements)

References 35 publications

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“…The [24] used previously in industrial settings [25]; applied to industry standards [26] [27]; and applied to cloud environments [27] [28]. The cost/benefits risk assessment of the project [2] was carried out by computing the Mean Failure Cost (MFC) for various UPS stakeholders addressing grid vulnerability, consequence, and risk analysis.…”

Section: Process and Resultsmentioning

confidence: 99%

Microgrid Disaster Resiliency Analysis: Reducing Costs in Continuity of Operations (COOP) Planning

Abercrombie

Ollis

Sheldon

et al. 2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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The electric grid serves a vital role in the supply chain of nearly all industrial and commercial organizations. A Microgrid infrastructure can provide this service and beneficial non-emergency services including a variety of generation/energy sources. To demonstrate the applicability of microgrids for energy resiliency, we present a microgrid resiliency case study for United Parcel Service's (UPS) three separate shipping facilities. The goal, to enhance energy security, minimize cost and prevent cascading losses within other related business units. The impacts and consequences of which are quantified in this study using a Mean Failure Cost (MFC) risk assessment measure. MFC accounts for the potential loses to identified stakeholders that may result from a set of identified failures due to a set of identified threats. In this case, our study uses a method we call All Hazards Econometric System (AHES). AHES incorporates the cost of COOP using a strategy that considers the payback period of microgrid installation as compared to other energy delivery strategies.

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Section: Process and Resultsmentioning

confidence: 99%

Microgrid Disaster Resiliency Analysis: Reducing Costs in Continuity of Operations (COOP) Planning

Abercrombie

Ollis

Sheldon

et al. 2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…Using the probability determined in this way, it is possible to state the formula which estimates the risk [68,69]:…”

Section: Risk Analysismentioning

confidence: 99%

Security Challenges in Industry 4.0 PLC Systems

2021

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The concept of the fourth industrial revolution assumes the integration of people and digitally controlled machines with the Internet and information technologies. At the end of 2015, more than 20 billion machines and devices were connected to the Internet, with an expected growth to half a trillion by 2030. The most important raw material for this digital revolution is data, which when properly stored, analyzed and secured, constitute the basis for the development of any business. In times of rapid industrial development, automation of production processes and systems integration via networks, the effective protection of the cyber-physical systems of a plant is particularly important. To minimize the risks associated with Internet access, one must define all the possible threats and determine their sources in the plant and block or minimize the possibility of sabotage or data loss. This article analyzes the security measures used in industrial systems. In particular, risk management and the study of the risk sources in terms of human, hardware and software aspects in networked PLC and SCADA systems are discussed. Methods of improving the architecture of industrial networks and their management are proposed in order to increase the level of security. Additionally, the safety of the communication protocols with PLCs in industrial control systems is discussed.

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“…Leveraging the definitions just presented, and to qualify the impact of dependencies between EDS assets, we developed a Dependency Matrix inspired in part by the matrix that qualifies availability developed by Chen et al [2]. This matrix allows the security relationships between all assets within a system to be qualified by specific factors.…”

Section: Dependency Matrixmentioning

confidence: 99%

“…For example, the MTU is considered in an acceptable state of security if its ExSol score is within the range of 2,000 to 4,500. However, in part (2), an attacker has discovered a vulnerability in the third system. As a response, collaborators come together and, using ExSol, determine that the RTU and Firewall security configurations have been taken advantage of.…”

Section: Example Use Casementioning

confidence: 99%

ExSol

et al. 2021

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No longer just prophesied about, cyber-attacks to Energy Delivery Systems (EDS) (e.g., the power grid, gas and oil industries) are now very real dangers that result in non-trivial economical losses and inconveniences to modern societies. In such a context, risk analysis has been proposed as a valuable way to identify, analyze, and mitigate potential vulnerabilities, threats, and attack vectors. However, performing risk analysis for EDS is difficult due to their innate structural diversity and interdependencies, along with an always-increasing threatscape. Therefore, there is a need for a methodology to evaluate the current system state, identify vulnerabilities, and qualify risk at multiple granularities in a collaborative manner among different actors in the context of EDS. With this in mind, this article presents ExSol , a collaborative, real-time, risk assessment ecosystem that features an approach for modeling real-life EDS infrastructures, an ontology traversal technique that retrieves well-defined security requirements from well-reputed documents on cyber-protection for EDS infrastructures, as well as a methodology for calculating risk for a single asset and for an entire system. Moreover, we also provide experimental evidence involving a series of attack scenarios in both simulated and real-world EDS environments, which ultimately encourage the adoption of ExSol in practice.

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Risk Assessment For Industrial Control Systems Quantifying Availability Using Mean Failure Cost (MFC)

Cited by 19 publications

References 35 publications

Microgrid Disaster Resiliency Analysis: Reducing Costs in Continuity of Operations (COOP) Planning

Microgrid Disaster Resiliency Analysis: Reducing Costs in Continuity of Operations (COOP) Planning

Security Challenges in Industry 4.0 PLC Systems

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