Applied Sciences, Vol. 13, Pages 6327: Fast, Lightweight, and Efficient Cybersecurity Optimization for Tactical–Operational Management

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Applied Sciences, Vol. 13, Pages 6327: Fast, Lightweight, and Efficient Cybersecurity Optimization for Tactical–Operational Management

Applied Sciences doi: 10.3390/app13106327

Authors:
Manuel Domínguez-Dorado
David Cortés-Polo
Javier Carmona-Murillo
Francisco J. Rodríguez-Pérez
Jesús Galeano-Brajones

The increase in frequency and complexity of cyberattacks has heightened concerns regarding cybersecurity and created an urgent need for organizations to take action. To effectively address this challenge, a comprehensive and integrated approach is required involving a cross-functional cybersecurity workforce that spans tactical and operational levels. In this context there can be various combinations of cybersecurity actions that affect different functional domains and that allow for meeting the established requirements. In these cases, agreement will be needed, but finding high-quality combinations requires analysis from all perspectives on a case-by-case basis. With a large number of cybersecurity factors to consider, the size of the search space of potential combinations becomes unmanageable without automation. To solve this issue, we propose Fast, Lightweight, and Efficient Cybersecurity Optimization (FLECO), an adaptive, constrained, and multi-objective genetic algorithm that reduces the time required to identify sets of high-quality cybersecurity actions. FLECO enables productive discussions on viable solutions by the cross-functional cybersecurity workforce within an organization, fostering managing meetings where decisions are taken and boosting the overall cybersecurity management process. Our proposal is novel in its application of evolutionary computing to solve a managerial issue in cybersecurity and enhance the tactical–operational cybersecurity management process.

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