We put forward a novel paradigm for preserving privacy in data outsourcing which departs from encryption. The basic idea behind our proposal is to involve the owner in storing a limited portion of the data, and maintaining all data (either at the owner or at external servers) in the clear. We assume a relational context, where the data to be outsourced is contained in a relational table. We then analyze how the relational table can be fragmented, minimizing the load for the data owner. We propose several metrics and present a general framework capturing all of them, with a corresponding algorithm finding a heuristic solution to a family of NP-hard problems. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Ciriani, V., De Capitani Di Vimercati, S., Foresti, S., Jajodia, S., Paraboschi, S., & Samarati, P. (2009). Keep a few: Outsourcing data while maintaining confidentiality. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5789 LNCS, pp. 440–455). https://doi.org/10.1007/978-3-642-04444-1_27
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