El componente social de la amenaza híbrida y su detección con modelos bayesianos/ The Social Component of the Hybrid Threat and its Detection with Bayesian Models

Palabras clave: inferencia bayesiana, redes bayesianas, seguridad informática, redes sociales, inteligencia artificial.

Resumen

Las sociedades contemporáneas están cada vez más condicionadas por el desarrollo de la tecnología informática. Esa tendencia deja entrever un panorama en el que cada ser humano se identifica por el binomio persona-computadora, mientras que la mayor informatización de la vida civil está generando ingentes cantidades de datos que son susceptibles de ser gestionados con fines bélicos. El objetivo de este artículo es abordar la utilidad potencial de las redes bayesianas como herramientas destinadas a la monitorización y detección temprana de ataques híbridos de carácter social a escala global. Como conclusión, planteamos que el uso de la inferencia y las redes bayesianas es útil para monitorear, detectar y supervisar el componente social de las amenazas híbridas a escala global por medio del análisis de las redes sociales.

Abstract

Contemporary societies are increasingly conditioned by the development of computer technology. This trend suggests a picture in which each human being is identified by the person-computer binomial while greater computerization of civil life is generating huge amounts of data that are likely to be managed for war purposes. The objective of this article is to address the potential utility of Bayesian networks aimed at monitoring and early detection of hybrid attacks of a global nature. We conclude that the use of inference and Bayesian networks is useful for monitoring, detection and supervision of the social component of hybrid threats globally through social network analysis.

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Publicado
2019-11-27
Cómo citar
Ruiz-Ruano, A.-M., López-Puga, J., & Delgado-Morán, J.-J. (2019). El componente social de la amenaza híbrida y su detección con modelos bayesianos/ The Social Component of the Hybrid Threat and its Detection with Bayesian Models. URVIO. Revista Latinoamericana De Estudios De Seguridad, (25), 57-69. https://doi.org/10.17141/urvio.25.2019.3997