P-Sensitive K-Anonymity with Generalization Constraints
Transactions on Data Privacy
Preventing range disclosure in k-anonymised data
Expert Systems with Applications: An International Journal
A user-oriented anonymization mechanism for public data
DPM'10/SETOP'10 Proceedings of the 5th international Workshop on data privacy management, and 3rd international conference on Autonomous spontaneous security
Utility-preserving transaction data anonymization with low information loss
Expert Systems with Applications: An International Journal
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In this paper, we propose a novel preference-constrained approach to k-anonymisation. In contrast to the existing works on k-anonymisation which attempt to satisfy a minimum level of protection requirement as a constraint and then optimise data utility within that constraint, we allow data owners and users to specify their detailed protection and usage requirements as a set of preferences on attributes or data values, treat such preferences as constraints and solve them as a multi-objective optimisation problem. This ensures that anonymised data will be actually useful to data users in their applications and sufficiently protected for data owners. Our preliminary experiments show that our method is capable of producing anonymisations that satisfy a range of preferences and have a high level of data utility and protection.