Towards Privacy-preserving Attribute Aggregation in Federated eID Systems

In: S. España, M. Ivanović, M. Savić (eds.): Proceedings of the CAiSE’16 Forum at the 28th International Conference on Advanced Information Systems Engineering, Ljubljana, Slovenia, 13-17.6.2016, published at http://ceur-ws.org Abstract. During the past years, achieving interoperability, i.e. creating identity federations, between different eID systems has gained relevance. A key problem of identity federations is the missing harmonization between different attribute providers (APs). In closed eID systems, ontologies allow a higher degree of automation in the process of aligning and aggregating attributes from different APs. This approach does not work for identity federations, as each eID system uses its own ontology to represent attributes. Moreover, providing attributes to intermediate entities required to align and aggregate attributes potentially violates privacy rules. To tackle these problems, we propose the use of combined ontology alignment approaches and locality-sensitive hashing (LSH) functions. We assess existing implementations of these concepts by means of criteria that are specific for identity federations. Obtained results show that suitable implementations of these concepts exist and that they can be used to achieve interoperability between eID systems on attribute level.