Many privacy preserving data mining algorithms attempt to selectively hide what database owners consider as sensitive. Specifically, in the association-rules domain, many of these ...
Recently, privacy issues have become important in clustering analysis, especially when data is horizontally partitioned over several parties. Associative queries are the core retr...
This paper presents a model for privacy preserving access control which is based on variety of purposes. Conditional purpose is applied along with allowed purpose and prohibited p...
Random perturbation is a promising technique for privacy preserving data mining. It retains an original sensitive value with a certain probability and replaces it with a random va...
Healthcare organisations practicing evidence-based medicine strive to unite their data assets in order to achieve a wider knowledge base for more sophisticated research as well as...