A semantic privacy-preserving model for data sharing and integration

Abstract

In this paper, we encompass and extend previous ontology-based data integration system. A semantic privacy-preserving model provides authorized view-based query answering over a widespread multiple servers for data sharing and integration. The combined semantics-enabled privacy protection policies are used to empower the data integration and access control services at the virtual platform (VP). The ontology mapping and merging algorithm with a local-as-view (LAV) source description that creates a global ontology schema at the VP by integrating multiple local ontology schemas for data sharing. The perfect rules integration of datalog rules enforces the data query and protection services. Semantics-enable policies are combined together at the VP, but the access control criteria specified in each server are still satisfied. Therefore the soundness and completeness of data sharing and protection criteria are ensured to support the validity of policy combination. This guarantees the trustworthiness of data sharing and protection services in multiple servers.