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Control de seguridad para sistemas de control en red con ataques de engaño: Un enfoque de control predictivo

Zhaoke Ning¹, Xinglian Zhou², Juncong Yang³

¹Key Laboratory of Advanced Spatial Mechanism and Intelligent Spacecraft, Ministry of Education, School of Aeronautics and Astronautics, Sichuan University, Chengdu 610207, China.

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Resumen

Este resumen es generado por máquina.

Este estudio presenta un método de control de seguridad robusto para sistemas de control en red que se enfrentan a ataques de engaño estocásticos. El enfoque utiliza optimización robusta de distribución y restricciones de probabilidad para mejorar la seguridad y el rendimiento del sistema.

Palabras clave:

restricciones de probabilidad ataques de engaño optimización robusta de distribución control de seguridad control predictivo estocástico por modelos

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Área de la Ciencia:

Ingeniería de Control
Ciberseguridad
Teoría de la Optimización

Sus antecedentes:

Los sistemas de control en red son vulnerables a sofisticados ataques de engaño.
Los métodos existentes a menudo tienen dificultades con señales de ataque estocásticas de límites desconocidos.

Objetivo del estudio:

Diseñar una metodología innovadora de control de seguridad para sistemas de control lineales en red (LNCS) bajo ataques de engaño estocásticos.
Mitigar el conservadurismo en el diseño del control de seguridad empleando restricciones de probabilidad.

Principales métodos:

Introdujo un conjunto de ambigüedad para caracterizar posibles señales de engaño utilizando restricciones de media-covarianza.
Formuló restricciones de probabilidad sobre las variables de estado y control del sistema.
Aplicó optimización robusta de distribución para una reformulación convexa determinista.
Utilizó control predictivo estocástico por modelos (SMPC) para la factibilidad recursiva y la convergencia.

Principales resultados:

Abordó con éxito ataques de engaño estocásticos de límites desconocidos.
Mitigó el conservadurismo en el diseño del control de seguridad.
Demostró la factibilidad recursiva y la convergencia del sistema controlado.
Validó la superioridad del enfoque a través de simulaciones en un convertidor elevador DC-DC.

Conclusiones:

La metodología de control de seguridad propuesta mejora eficazmente la resiliencia de los LNCS contra ataques de engaño estocásticos.
La integración de conjuntos de ambigüedad, restricciones de probabilidad y SMPC ofrece una dirección prometedora para el diseño de sistemas de control robustos.