La Guerra Silenciosa de la Ciberseguridad Satelital mediante Inteligencia Artificial: Un Análisis del Estado del Arte
DOI:
https://doi.org/10.61616/rvdc.v7i2.1553Palavras-chave:
ciberseguridad satelital, aprendizaje profundo, inteligencia artificial, seguridad informática, procesamiento de datosResumo
El advenimiento del NewSpace y la emergencia de la Inteligencia Artificial (IA) ofensiva han expandido exponencialmente la superficie de ataque en la infraestructura satelital, volviendo obsoletas las defensas basadas en reglas estáticas. El objetivo de este artículo es analizar críticamente el estado del arte de la ciberseguridad satelital mediada por IA. Bajo un enfoque cualitativo y propositivo, se ejecutó una revisión sistemática de la literatura guiada por las directrices PRISMA y Kitchenham sobre un corpus estratificado de 28 fuentes primarias de alta fidelidad (2021-2026). Los resultados identifican una taxonomía de amenazas autónomas en los frentes de software de vuelo, enlace y red. Se demuestra que los modelos de aprendizaje profundo (Deep Learning) superan el colapso operativo de las firmas tradicionales, alcanzando una efectividad analítica ( F1 -score) superior al 94.8% en la detección de anomalías a bordo en condiciones de pérdida de señal. Asimismo, se concluye que la viabilidad del despliegue en órbita ante restricciones físicas (SWaP) exige optimizaciones de TinyML (cuantización a INT8) y esquemas de monitoreo pasivo integrados con los estándares internacionales CCSDS y NIST, fundamentando la transición indispensable hacia la autonomía defensiva y el resguardo de la soberanía digital espacial.
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Copyright (c) 2026 Juan Rigoberto Castillo Serracín, Javier Miguel Gómez
Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.
