Cell Suppression: Experience and Theory
Inference Control in Statistical Databases, From Theory to Practice
A critique of the sensitivity rules usually employed for statistical table protection
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Privacy, accuracy, and consistency too: a holistic solution to contingency table release
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Computer Methods and Programs in Biomedicine
Differential privacy and robust statistics
Proceedings of the forty-first annual ACM symposium on Theory of computing
Privacy: Theory meets Practice on the Map
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Regression output from a remote analysis server
Data & Knowledge Engineering
Asymptotically Optimal and Private Statistical Estimation
CANS '09 Proceedings of the 8th International Conference on Cryptology and Network Security
Establishing an infrastructure for remote access to microdata at Eurostat
PSD'10 Proceedings of the 2010 international conference on Privacy in statistical databases
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Calibrating noise to sensitivity in private data analysis
TCC'06 Proceedings of the Third conference on Theory of Cryptography
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In this paper we provide an introduction to the area of disseminating spatial data through maps, including an overview of confidentialisation techniques. To date, published methods have focussed on confidentialising maps of spatial point data, mainly in the context of epidemiological and health research. However, maps of spatial data sets of point and diffuse (line and area) records are becoming more important and require confidentialisation in some applications. In this paper we propose a method for confidentialising maps of spatial data sets which include a mixture of point, line and area records. The method combines and adapts traditional non-perturbative disclosure control techniques.