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Towards effective cybersecurity resource allocation: the Monte Carlo predictive modelling approach

Towards effective cybersecurity resource allocation: the Monte Carlo predictive modelling approach Organisations invest in technical and procedural capabilities to ensure the confidentiality, integrity and availability of information assets and sustain business continuity at all times. However, given growing productive assets and limited protective security budgets, there is a need for deliberate evaluation of information security investment. Optimal resource allocation to security is often affected by intrinsically uncertain variables, leading to disparities in resource allocation decisions. We explored how Monte Carlo predictive simulation model can be used within the context of information technology to reduce these disparities. Using a conceptual enterprise as a case study and verifiable historical cost of security breaches as parametric values, our model shows why using conventional risk assessment approach as budgeting process can result in significant over/under allocation of resources for cyber capabilities. Our model can serve as a benchmark for policy and decision support to aid stakeholders in optimising resource allocation for cyber security investments. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Critical Infrastructures Inderscience Publishers

Towards effective cybersecurity resource allocation: the Monte Carlo predictive modelling approach

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1475-3219
eISSN
1741-8038
DOI
10.1504/IJCIS.2017.088235
Publisher site
See Article on Publisher Site

Abstract

Organisations invest in technical and procedural capabilities to ensure the confidentiality, integrity and availability of information assets and sustain business continuity at all times. However, given growing productive assets and limited protective security budgets, there is a need for deliberate evaluation of information security investment. Optimal resource allocation to security is often affected by intrinsically uncertain variables, leading to disparities in resource allocation decisions. We explored how Monte Carlo predictive simulation model can be used within the context of information technology to reduce these disparities. Using a conceptual enterprise as a case study and verifiable historical cost of security breaches as parametric values, our model shows why using conventional risk assessment approach as budgeting process can result in significant over/under allocation of resources for cyber capabilities. Our model can serve as a benchmark for policy and decision support to aid stakeholders in optimising resource allocation for cyber security investments.

Journal

International Journal of Critical InfrastructuresInderscience Publishers

Published: Jan 1, 2017

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