面向流程工业控制的双安融合知识图谱研究

With the development of industrial control systems,security issues in these systems have become increasingly important.However,traditional industrial safety systems usually focus on either information security or production safety,thus failing to consider both issues at the same time.As structured representation of data,knowledge graph(KG) is capable of hosting domain-specific knowledge and modeling causal relationships among knowledge.However,most studies leverage KG to handle cybersecurity,while rarely pay attention to information security and production safety problems in industrial control systems.This paper proposes a set of construction methods for dual-security KG for process industrial control systems.Using the techniques of named entity recognition and relation extraction,it builds a large number of dual-security knowledge triples from a real-world production corpus.The built KG incorporates both features of chemical industry production process and potential network security flaws,providing comprehensive security guarantee for industrial control system.