2008 Third International Conference on Availability, Reliability and Security (2008)
Mar. 4, 2008 to Mar. 7, 2008
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ARES.2008.87
Data protection mechanisms need to find a trade-off between information loss and disclosure risk. To this end, information loss and disclosure risk measures have been developed. Due to the fact that when data is published it is usual to ignore which kind of analyses a user will pursue with the data, generic information loss measures are used to analyse the impact of the perturbation method onto the data. Such generic information loss measures are defined in terms of a few general-enough statistics. Nevertheless, a more fine-grained analysis is needed for particular data uses. In this paper we provide the reader with a review of a few results on cluster-specific information loss measures. More specifically, we consider the case of using fuzzy clustering to the perturbated data.
Privacy, clustering, data mining
S. Ladra and V. Torra, "Cluster-Specific Information Loss Measures in Data Privacy: A Review," 2008 Third International Conference on Availability, Reliability and Security(ARES), vol. 00, no. , pp. 994-999, 2008.