Research on Data Security Service Support System for Industrial Sector

Abstract

Industrial data security confronts multifaceted threats stemming from technical vulnerabilities, management deficiencies, and human
risks. These threats make traditional protection systems unable to meet dynamic security demands. This study proposes the construction of
a security management system covering the whole life cycle of data, integrating technologies such as quantum cryptography and blockchain
verification to ensure secure data flow. It also develops an intelligent monitoring system based on deep learning to shift from passive defense
to active prediction, and designs a multi-level identity authentication mechanism to balance the needs of open sharing and security isolation
in industrial scenarios. The implementation path emphasizes the combination of technological innovation and scenario validation, alongside
industrial chain collaboration and standard development, forming a comprehensive solution that includes breakthroughs in cryptographic
algorithms, ecological joint defense mechanism, and intelligent compliance systems. This provides security assurance for industrial digital
transformation.