Arquitectura de seguridad multinivel con enfoque predictivo para sistemas de almacenamiento distribuido en infraestructuras Cloud

Diana Carolina Decimavilla-Alarcón; Enrique Joel Murillo-Ávila

Autores/as

Diana Carolina Decimavilla-Alarcón Instituto Superior Tecnológico Vicente Rocafuerte. Ecuador. https://orcid.org/0000-0002-0375-0216
Enrique Joel Murillo-Ávila Instituto Superior Tecnológico Vicente Rocafuerte. Ecuador. https://orcid.org/0009-0007-1552-1713

Palabras clave:

Seguridad multinivel, machine learning predictivo, almacenamiento distribuido, ciberseguridad Cloud, arquitecturas adaptativas

Resumen

El estudio desarrolla un análisis comprehensivo de arquitecturas de seguridad multinivel con capacidades predictivas para sistemas de almacenamiento distribuido en entornos cloud computing, la investigación se centra específicamente en analizar exhaustivamente la literatura existente sobre estrategias de seguridad multinivel y evaluar comparativamente diferentes modelos de arquitecturas de seguridad predictiva, metodológicamente, se adopta un enfoque cualitativo con diseño descriptivo-exploratorio, fundamentado en una revisión sistemática de literatura científica de bases de datos reconocidas como IEEE Xplore, ACM Digital Library y ScienceDirect. El análisis implementa un método interpretativo para identificar patrones y tendencias, categorizando sistemáticamente los hallazgos en diferentes dimensiones mediante matrices comparativas que evalúan aspectos como precisión predictiva, escalabilidad, tiempo de respuesta y consumo de recursos, los principales hallazgos revelan una clara evolución desde arquitecturas tradicionales basadas en seguridad perimetral hacia enfoques más sofisticados y adaptativos, además, se destaca que los modelos basados en técnicas de ensemble learning, particularmente Random Forest, demuestran una precisión superior en la detección de amenazas y anomalías.

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