A Knowledge Graph Approach to Cyber Threat Mitigation Derived from Data Flow Diagrams

Data Flow Diagrams (DFD) have proven effective in designing and analyzing the flow of data in enterprise systems. They serve as indispensable tools for enterprises that are undergoing transition to cloud services. DFDs aid in understanding the current processes, identifying interfaces and integration points that require security measures. This paper reports a Design Science project to mitigate the cyber security threats at the design phase of a system and to perform auditing of an existing system through knowledge graphs. The proposal leverages knowledge gathered from various sources in a knowledge graph to identify semantic relationships and patterns, enabling automated inference, analysis and detection of vulnerability patterns. Furthermore, LLM-based (large language models) capabilities transform data management details captured as Data Flow Diagrams (DFD) into knowledge graphs for semantic querying and improved decision support.