Defining a Cyber Resilience Investment Strategy in an Industrial Internet of Things Context†
AbstractThe fourth industrial revolution has brought several risks to factories along with its plethora of benefits. The convergence of new technologies, legacy technologies, information technologies and operational technologies in the same network generates a wide attack surface. At the same time, factories need continuous production to meet their customers’ demand, so any stopped production can have harsh effects on a factory’s economy. This makes cyber resilience a key requirement in factories nowadays. However, it is difficult for managers to define effective cyber resilience strategies, especially considering the difficulty of estimating adequate investment in cyber resilience policies before the company has suffered cyber incidents. In this sense, the purpose of this article is to define and model an effective cyber resilience strategy. To achieve this, the system dynamics methodology was followed in order to get five experts’ opinions on the best strategy to invest in cyber resilience. Interviews were conducted with these experts; their reasoning was put into behavior over time graphs and a system dynamics model was built from these findings. The main conclusion is that a cyber resilience investment strategy should be dynamic, investing in both technical security and personnel training, but at first with an emphasis on technical security and later shifting to have an emphasis on training. View Full-Text
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Carías, J.F.; Labaka, L.; Sarriegi, J.M.; Hernantes, J. Defining a Cyber Resilience Investment Strategy in an Industrial Internet of Things Context. Sensors 2019, 19, 138.
Carías JF, Labaka L, Sarriegi JM, Hernantes J. Defining a Cyber Resilience Investment Strategy in an Industrial Internet of Things Context. Sensors. 2019; 19(1):138.Chicago/Turabian Style
Carías, Juan F.; Labaka, Leire; Sarriegi, José M.; Hernantes, Josune. 2019. "Defining a Cyber Resilience Investment Strategy in an Industrial Internet of Things Context." Sensors 19, no. 1: 138.
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