Efficient Access Control of Large Scale RDF Data Using Prefix-Based Labeling

A massive amount of resource description framework (RDF) data are available on the web. An RDF data publisher may want to prevent a few users from accessing a certain part of the RDF data. Various approaches have been proposed to reject a given SPARQL query that is intended to access instances or classes that are required to be protected. The problem of such access control management can be cast to processing ancestor/descendant relationship query over class hierarchy. The prefix-based labeling scheme has been applied to the fast processing of ancestor/descendant relationship queries. However, we observed that the existing approaches are ineffective in dealing with massive amounts of RDF data because the adopted labeling schemes produce labels of large sizes. Hence, we adopted the state-of-the art MapReduce-based algorithm for prefix-based labeling to reduce the label size based on the structural information of RDF data. Experiments with real-world RDF datasets showed that the proposed approach is more efficient than the conventional methods.