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This paper proposes an ontology-based information content security analysis framework, which adopts artificial intelligent system designing theory and ontology engineering method to improve information content security surveillance. This framework introduces ICSO (information content security ontology), by which we incorporate disparate and heterogeneous data sources into surveillance system , and an novel reasoning subsystem to utilize ICSO knowledge to support information content security surveillance in interpreting surveillance data and improving surveillance decision making. The ICSO is not only a knowledge base but also a SNA (social network analysis) model, thus we could easily implement relative SNA methods to focuses on individualpsilas computer mediated communication (CMC) networks to effectively spot harmful characters. And we test our system on Enron Email Dataset and web pages, the result shows this framework is an efficient and effective solution in information content security and can be spread to other knowledge-based systems.