Secure Access Control in Semantic Web-Based E-Government Systems

The rapid growth of semantic web technologies has led to their widespread adoption in e-government applications, addressing challenges related to administrative heterogeneity. However, integrating semantic web techniques into these applications introduces security vulnerabilities, particularly in access control mechanisms. This research proposes a secure access control solution for semantic web-based e-government systems. The proposed approach enhances the Flat Role-Based Access Control (Flat RBAC) model by incorporating ontology-driven methodologies and semantic reasoning. Domain-specific ontologies were developed to model the information of participating government entities, while a centralized ontology was designed to precisely define user roles and permissions. By leveraging semantic web technologies such as RDF (Resource Description Framework), OWL (Ontology Web Language), and SPARQL (SPARQL Protocol and RDF Query Language), the system enforces access policies dynamically and with semantic flexibility. The solution utilizes Apache Jena Fuseki as a triple store to facilitate interoperability among government agencies while ensuring that unauthorized access is prevented through semantic-based authentication. Additionally, a reasoning engine is employed to infer implicit facts from existing data, enhancing query responses and logical inference capabilities. The system was qualitatively assessed based on standard e-government criteria, confirming its support for flexible policy updates, secure access control, and semantic interoperability. In conclusion, this study provides a robust access control framework for e-government environments, demonstrating significant improvements in data interoperability and security management. These findings pave the way for future research on optimizing system performance and extending the approach to advanced access control models such as Hierarchical RBAC and Constrained RBAC.