Pantaleone Nespoli, Félix Gómez Mármol, Jorge Maestre Vidal
IEEE Access, vol. 9, pp. 60971-60996
Publication year: 2021

Abstract

Nowadays, Information and Communication Technology (ICT) infrastructures play a crucial role for human beings, providing essential services at astonishing speed. Nevertheless, such a centrality of those infrastructures attracts the interest of ill-motivated actors that target such infrastructures with cyberattacks that are every day more sophisticated and more disruptive. In this alarming context, selecting the optimal set of countermeasures represents a primary need to react against the appearance of potentially dangerous threats effectively. With the motivation to contribute to developing faster and more effective response capabilities against them, the paper at hand introduces a novel cybersecurity reaction methodology based on Artificial Immune Systems (AIS), for which the evolutionary computing paradigm has been adopted. By leveraging the outstanding properties of these bio-inspired techniques, the selected countermeasures to defeat cyberthreats through cloning and mutation phases in an effort to improve the quality of the solution from a quantitative perspective, being able to adjust the risk to which the assets of the protected system are exposed. Exhaustive experiments demonstrate the feasibility of the proposed approach, reducing the risk in a more than acceptable time lapse.

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Co-Authors

This work would not have been possible without the inestimable contribution of:

  • Pantaleone Nespoli
  • Jorge Maestre Vidal

Pantaleone Nespoli

Pantaleone Nespoli

University of Murcia

Web

Jorge Maestre Vidal

Jorge Maestre Vidal

Indra Digital Labs

Web

Citation

Pantaleone Nespoli, Félix Gómez Mármol, Jorge Maestre Vidal, «A bio-inspired reaction against cyberattacks: AIS-powered optimal countermeasures selection«, IEEE Access, vol. 9, pp. 60971-60996, 2021

Journal Ranking & Impact Factor

  • Journal: IEEE Access
  • Category: Engineering, Electrical & Electronic
  • Rank: 105/276
  • Quartile: Q2
  • Impact Factor: 3.476