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Research on network identity association and character relationship portrait based on case-oriented big data

Due to the emergence of highly intelligent new cybercriminals in the Internet, traditional case investigation methods cannot analyze the massive amount of data efficiently and accurately. Therefore, we can use relevant technology of big data to conduct correlation analysis on the network identities of the people involved, describe the relationship between the characters, and study the overlapping communities based on the separation of multiple roles. Then, according to the features that the ontology of the users involved and the associated targets contains multiple roles, the high-value targets hidden in the case can be mined. By mining, analyzing, and modeling the big data involved in the case, and constructing a portrait of the relationship between personal identities, it is possible to give an early warning and judgment on potential criminal tendencies, and to carry out demonstration applications in the public security system to combat complex new cybercrimes.