Enterprise Information Fusion and Security Audit Method Based on DBSCAN Clustering

With the aim of improving the processing and auditing effectiveness of enterprise information, this study designs an enterprise information fusion and security auditing method based on DBSCAN clustering. Firstly, the enterprise text information classification process is determined through word segmentation processing, and the enterprise text information is subjected to corpus balance processing to effectively solve the problem of data skewness that may exist in the enterprise text information; Then, based on the classification results and taking the relevant interests of the enterprise as the benchmark, the DBSCAN clustering algorithm is used to determine the distribution density of key audit features, integrate and process enterprise information, and make the clustering results more closely related to the actual operational situation of the enterprise; Finally, based on the clustering of information and the theory of correlated data, design a security audit model. In the experiment, multiple departments within M enterprise are taken as the test objects, and their data information in the past three months is fused and audited. The results show that the method can meet the internal security audit needs of enterprises and has application value.