{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T17:17:49Z","timestamp":1771003069564,"version":"3.50.1"},"reference-count":25,"publisher":"SAGE Publications","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"published-print":{"date-parts":[[2023,2,4]]},"abstract":"<jats:p>In order to improve the accuracy of hierarchical network security situational awareness data fusion and shorten the fusion time, this paper proposes a hierarchical network security situational awareness data fusion method in cloud computing environment. The hierarchical model is established to obtain the hierarchical structure of data fusion. Hierarchical network security situational awareness data are collected and processed in parallel by cloud computing technology. According to the data collection results, the similarity between security events is calculated by using the clustering idea, and the similar security events are merged to achieve the purpose of removing redundant events. The hierarchical network security situational awareness data is fused by grey relational analysis. Finally, the simulation results show that the accuracy of data fusion of this method is high, up to 98%, and the fusion time is short, the longest is 13 s. Compared with the comparison method, this method has a better performance, indicating that this method is suitable for data fusion of hierarchical network security situation awareness.<\/jats:p>","DOI":"10.3233\/jcm-226542","type":"journal-article","created":{"date-parts":[[2022,11,11]],"date-time":"2022-11-11T11:40:06Z","timestamp":1668166806000},"page":"237-251","source":"Crossref","is-referenced-by-count":6,"title":["Hierarchical network security situation awareness data fusion method in cloud computing environment"],"prefix":"10.1177","volume":"23","author":[{"given":"Hongwu","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Kai","family":"Kang","sequence":"additional","affiliation":[]},{"given":"Wei","family":"Bai","sequence":"additional","affiliation":[]}],"member":"179","reference":[{"key":"10.3233\/JCM-226542_ref1","doi-asserted-by":"crossref","unstructured":"Wang HT, Song LH, Liu J, Xiang TT. 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