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Software . 2026
License: CC BY NC
Data sources: Datacite
ZENODO
Software . 2026
License: CC BY NC
Data sources: Datacite
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Modelo de recuperación autónomo para entornos virtuales ante incidentes de seguridad

Authors: Solano Mora, David;

Modelo de recuperación autónomo para entornos virtuales ante incidentes de seguridad

Abstract

Este artefacto de software corresponde al script de orquestación validado en laboratorio, desarrollado como parte de una Tesis de Maestría en Ciberseguridad (2026). El proyecto es un modelo de recuperación autónoma diseñado para automatizar la restauración de sistemas virtualizados ante incidentes de seguridad. El presente script implementa la lógica de orquestación basada en Python que permite ejecutar acciones automatizadas de aislamiento, recolección de evidencia digital y restauración de snapshots en entornos VirtualBox. El diseño del modelo contempla su integración con herramientas de detección como Wazuh y con mecanismos de virtualización para la gestión de snapshots y restauración de máquinas virtuales. El objetivo principal de esta implementación es reducir el Tiempo Medio de Recuperación (MTTR) mientras se preserva evidencia forense durante incidentes de seguridad. Esta versión (v1.0.0) fue validada en un entorno de laboratorio controlado a lo largo de 20 ejecuciones consecutivas, demostrando un desempeño estable y consistente. Esta publicación representa la versión de laboratorio del script de orquestación. No incluye configuraciones completas de entorno, endurecimiento para producción ni controles empresariales de despliegue. Licencia: Creative Commons Atribución-NoComercial 4.0 Internacional (CC BY-NC 4.0)

Keywords

Cyber Resilience, Digital Forensics, Snapshot Recovery, Virtualization, Orchestration, Incident Response, MTTR, Wazuh

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average