Secure XML querying based on authorization graphs

• Published in: Information systems frontiers Vol. 14; no. 3; pp. 617 - 632
• Main Authors: Chebotko, Artem, Chang, Seunghan, Lu, Shiyong, Fotouhi, Farshad
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01-07-2012; Springer Nature B.V
• Subjects: Acceptability; Access control; Algorithms; Analysis; Authorizations; Business and Management; Computer science; Control; Extensible Markup Language; Information systems; IT in Business; Management of Computing and Information Systems; Network security; Operations Research/Decision Theory; Optimization techniques; Queries; Query processing; Recursive; Security; Studies; Systems Theory; XML; Access control; Authorization graph; Authorization model; Security; XML
• ISSN: 1387-3326; 1572-9419
• DOI: 10.1007/s10796-010-9289-2

XML is rapidly emerging as a standard for data representation and exchange over the World Wide Web and an increasing amount of sensitive business data is processed in XML format. Therefore, it is critical to have control mechanisms to restrict a user to access only the parts of XML documents that she is authorized to access. In this paper, we propose the first DTD-based access control model that employs graph matching to analyze if an input query is fully acceptable, fully rejectable, or partially acceptable. In this way, there will be no further security overhead for the processing of fully acceptable and rejectable queries. For partially acceptable queries, we propose a graph-matching based authorization model for an optimized rewriting procedure in which a recursive query (query with descendant axis ‘//’) will be rewritten into an equivalent recursive one if possible and into a non-recursive one only if necessary, resulting queries that can fully take advantage of structural join based query optimization techniques. Moreover, we propose an index structure for XML element types to speed up the query rewriting procedure, a facility that is potentially useful for applications with large DTDs. Our performance study results showed that our algorithms armed with rewriting indexes are promising.