The protection of personal privacy is paramount, and consequently many efforts have been devoted to the study of data protection techniques. Governments, statistical agencies and corporations must protect the privacy of the individuals while guaranteeing the right of the society to knowledge. Microaggregation is one of the most promising solutions to deal with this praiseworthy task. However, its high computational cost prevents its use with large amounts of data. In this article we propose a new microaggregation algorithm that uses self-organizing maps to scale down the computational costs while maintaining a reasonable loss of information.
Solanas, A., Gavalda, A., Rallo, R. (2009) Micro-SOM: A Linear-Time Multivariate Microaggregation Algorithm Based on Self-Organizing Maps. ICANN, Lecture Notes in Computer Science, 5768:525-535