A Semantic-based Inference Control Algorithm for RDF Stores Privacy Protection

摘要

Resource Description Framework (RDF) as a standard model of knowledge representation is bringing a technological revolution in the Semantic Web. For RDF stores, sensitive triples can be inferred from non-sensitive triples through entailments rules, which brings about a security problem that some users' information may be leaked. To solve this problem, a method of removing some non-sensitive triples with low access frequency to achieve inference control is studied by some researchers. However, access frequency of a triple is unstable and it can not fully represent the importance of semantic information. In this paper, the concept of Degree of triples and Semantic Value of triples are introduced according to RDF directed graph. An inference control algorithm based on Semantic Value and access frequency is proposed. Experimental results show that this algorithm can effectively prevent illegal inference and minimize the loss of semantic information.