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Updated: Jan 7, 2026

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Multiplicación de matrices por lotes segura y codificada localmente distribuida

Haobo Jia1, Zhuqing Jia1

  • 1School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China.

Entropy (Basel, Switzerland)
|December 24, 2025
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio presenta un nuevo método para la multiplicación segura de matrices distribuida, que permite el procesamiento eficiente por lotes incluso con nodos trabajadores poco fiables. El esquema garantiza la privacidad de los datos y tolera retrasos del sistema y participantes maliciosos.

Palabras clave:
multiplicación de matrices por loteseficiencia de comunicación y computaciónpatrón de codificación localcomputación distribuida seguratolerancia a retrasos

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Área de la Ciencia:

  • Computación distribuida
  • Teoría de la información
  • Criptografía

Sus antecedentes:

  • La multiplicación de matrices por lotes requiere una gran cantidad de cómputo.
  • Los sistemas distribuidos enfrentan desafíos con los nodos lentos (stragglers) y los nodos que colaboran.
  • Los métodos existentes para la multiplicación de matrices por lotes distribuida codificada (CDBMM) tienen limitaciones en escenarios seguros de múltiples lotes.

Objetivo del estudio:

  • Desarrollar el primer esquema para la multiplicación segura de matrices por lotes distribuida y codificada localmente (LESDBMM).
  • Permitir la computación eficiente y segura de múltiples lotes de productos matriciales en un entorno distribuido.
  • Manejar los nodos lentos y los trabajadores que colaboran manteniendo la privacidad de los datos.

Principales métodos:

  • Utiliza códigos de subespacio cruzado (CSA) y un modelador nulo CSA.
  • Propone un esquema novedoso para LESDBMM con capacidades de procesamiento por lotes.
  • Analiza el rendimiento en términos de nodos lentos tolerables, comunicación y computación.

Principales resultados:

  • El esquema LESDBMM propuesto es el primero de su tipo para el procesamiento por lotes.
  • Logra un rendimiento comparable a los códigos CSA para CDBMM cuando M=1 y X=0.
  • Demuestra un manejo efectivo de los nodos lentos y los trabajadores que colaboran.

Conclusiones:

  • El esquema desarrollado generaliza los códigos CSA para CDBMM al entorno LESDBMM.
  • Ofrece una solución robusta para cálculos matriciales seguros y eficientes a gran escala.
  • Avanza el campo de la computación distribuida codificada para operaciones matriciales complejas.