An Automatically Filtering Blacklist Model of Social Network Based on Semantic Web
Le Ha 1, Guo-Zi Sun 1,2
(1. College of Computer, Nanjing University of Posts ＆ Telecommunications, Nanjing 210003, China;2. Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing 210003, China)
Abstract:
According to the features of the semantic web technology, it is very suitable to solve the security issue of the current social network environment. Firstly, in this paper, it extends the existing ontology model of the social network with some relevant classes, and introduces a brand new ontology which is used to represent the malicious information. After introducing these models, a method of identifying the malicious message is raised. Finally, the experiments and simulations analyze the feasibility of the whole system. The results validate that the malicious users can be automatically filtered, and some worthy digital evidence can be effectively provided to forensic investigators.
Key words: social network semantic web ontology OWL digital evidence
DOI：10.11916/j.issn.1005-9113.2014.06.013
Clc Number:TP391.7
Fund:
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An Automatically Filtering Blacklist Model of Social Network Based on Semantic Web
本站小编 哈尔滨工业大学/2019-10-24
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