Jenni Reuben Shanthamoorthy
Information retrieval enriched with knowledge representation and reasoning introduces novel privacy challenges such as inference of sensitive information from non-sensitive information. Hence, in my research I study the privacy threats in Semantic Web automated reasoning, and propose privacy preserving query-answering solutions.
Reuben, J., Fischer-Hübner, S. (2017). A Privacy Focused Formal Model of Authorization for Data Modeled using Semantic Web Technologies. In The 9th International Conference on Advances in Databases, Knowledge, and Data Applications, May 21 - May 25, 2017, Barcelona.
Reuben, J., Martucci, L. A., Fischer-Hübner, S., Packer, H., Hedbom, H., Moreau, L. (2016). Privacy Impact Assessment Template for Provenance. In The 11th International Conference on Availability, Reliability and Security (ARES 2016), August 31 – September 2, 2016, Salzburg. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-43020
Reuben, J., Martucci, L. A., Fischer-Hübner, S. (2016). Automated Log Audits for Privacy Compliance Validation : A Literature Survey. In Privacy and Identity Management. Time for a Revolution? : 10th IFIP WG 9.2, 9.5, 9.6/11.7, 11.4, 11.6/SIG 9.2.2 International Summer School, Edinburgh, UK, August 16-21, 2015, Revised Selected Papers (Vol. 476, pp. 312–326). https://doi.org/10.1007/978-3-319-41763-9_21