Abstract
Web services have emerged as an open standard-based means for publishing and sharing data through the Internet. Whenever web services disclose sensitive data to service consumers, data privacy becomes a fundamental concern for service providers. In many applications, sensitive data may only be disclosed to particular users for specific purposes. That is, access to sensitive data is often restricted, and web services must be aware of these restrictions such that the required privacy of sensitive data can be guaranteed. Privacy preservation is a major challenge that has attracted much attention by researchers and practitioners. Hippocratic databases have recently emerged to protect privacy in relational database systems where the access decisions, allowed or denied, are based on privacy policies and authorization tables. In particular, the specific purpose of a data access has been considered. Ontologies has been used to represent classification hierarchies, which can be efficiently accessed via ontology query languages. In this paper, we propose an ontology-based data access model so that different levels of data access can be provided to web service users with different roles for different purposes. For this, we utilize ontologies to represent purpose hierarchies and data generalization hierarchies. For more complex service requests that require composite web services we discuss the privacy-aware composition of web services. To demonstrate the usefulness of our access control model we have implemented prototypes of financial web services, and used them to evaluate the performance of the proposed approach.
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Hartmann, S., Ma, H., Vechsamutvaree, P. (2016). Providing Ontology-Based Privacy-Aware Data Access Through Web Services and Service Composition. In: Hameurlain, A., Küng, J., Wagner, R., Schewe, KD., Bosa, K. (eds) Transactions on Large-Scale Data- and Knowledge-Centered Systems XXX. Lecture Notes in Computer Science(), vol 10130. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54054-1_5
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