Research on security assessment based on big data and multi-entity profile

• Main Authors: Liu, Wenfu, Pang, Jianmin, Yang, Shudan, Li, Nan, Du, Qiming, Sun, Daozhu, Liu, Fudong
• Format: Conference Proceeding
• Language: English
• Subjects: Big Data; Data mining; entity portrait; Evaluation process; Personnel; Risk management; Security; security assessment; Spark; Training; Transportation
• ISSN: 2689-6621
• DOI: 10.1109/IAEAC50856.2021.9391153

Security assessment is one of the important problems, especially in the fields of military training, transportation and network management. The security "related parties" (entities in this paper) have internal relations in the three fields. It is of great significance of constructing the attributes of these entities or even designing a unified security assessment method. Security assessment in these areas has been studied and explored for a long time. However, the research is relatively scattered and unilateral. It is no unified and reusable method from data collection to security assessment. Based on the advantages of big data technology in the storage and analysis of massive data, the paper proposed a security risk element acquisition method from data collection and preprocessing, storage and mining to attribute extraction and aggregation. In addition, drawing on the idea of user portraits in other fields, constructed personnel entities, equipment entities and "other" entity labels related to security risks. Finally, a security risk assessment process based on these entities is designed.