Research on multi-source heterogeneous data structure analysis technique based on AI security detection algorithm

The relationships between multi-source heterogeneous data and elements in the field of artificial intelligence security are integrated and analyzed in this paper, including attack information, data information, and other security data. Targeting the associated complex entity concepts that existed in the construction of the artificial intelligence security knowledge graph, the ontology structure is divided into theory layer, problem layer, and measure layer, making the artificial intelligence security ontology more diverse and expandable. The addition of the measure layer provides more accurate security decision-making reasoning for the subsequent knowledge inference stage.