Artículos
Prospectiva de seguridad de las redes de sensores inalámbricos
Fernando Gutiérrez-Portela- Florina Almenares-Mendoza
- Liliana Calderón-Benavides
- Efren Romero-Riaño
Publicado 2021-06-07
Palabras clave
- redes de sensores inalámbricos,
- ataques a las WSN,
- mecanismos de seguridad,
- inteligencia artificial,
- detección de intrusiones
- recursos computacionales,
- contramedidas,
- protocolo ZigBee,
- aprendizaje automático,
- técnicas supervisadas,
- técnicas no supervisadas,
- detección de anomalías,
- algoritmos de agrupamiento,
- VOSviewer,
- principios de seguridad ...Más
Cómo citar
Gutiérrez-Portela, F., Almenares-Mendoza, F., Calderón-Benavides, L., & Romero-Riaño, E. (2021). Prospectiva de seguridad de las redes de sensores inalámbricos. Revista UIS Ingenierías, 20(3), 189–202. https://doi.org/10.18273/revuin.v20n3-2021014
Resumen
En las Redes de Sensores Inalámbricos (WSN), los nodos son vulnerables a los ataques de seguridad porque están instalados en un entorno difícil, con energía y memoria limitadas, baja capacidad de procesamiento y transmisión de difusión media; por lo tanto, identificar las amenazas, los retos y las soluciones de seguridad y privacidad es un tema candente hoy en día. En este artículo se analizan los trabajos de investigación que se han realizado sobre los mecanismos de seguridad para la protección de las WSN frente a amenazas y ataques, así como las tendencias que surgen en otros países junto con futuras líneas de investigación. Desde el punto de vista metodológico, este análisis se muestra a través de la visualización y estudio de trabajos indexados en bases de datos como IEEE, ACM, Scopus y Springer, con un rango de 7 años como ventana de observación, desde 2013 hasta 2019. Se obtuvieron un total de 4.728 publicaciones, con un alto índice de colaboración entre China e India. La investigación planteó desarrollos, como avances en los principios de seguridad y mecanismos de defensa, que han llevado al diseño de contramedidas en la detección de intrusiones. Por último, los resultados muestran el interés de la comunidad científica y empresarial por el uso de la inteligencia artificial y el aprendizaje automático (ML) para optimizar las medidas de rendimiento.
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[13] A. Narmada, P. S. Rao, “Zigbee based WSN with IP connectivity,” In 2012 Fourth International Conference on Computational Intelligence, Modelling and Simulation, 2012, pp. 178-181. doi: 10.1109 / CIMSim.2012.39.
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