Research in Microaggregation Algorithms for k-Anonymization
YU Hui-qun · Dianzi xuebao · 2008
K-anonymization of tables is a method to prevent private information from disclosure prior to publication,which is achieved traditionally via generalization/suppression techniques.However,these methods have some defects on efficiency,availability,etc.Recently,microaggregation algorithm is proposed as an alternative to generalization/suppression method for k-anonymization whose goal is to cluster a set of records into groups of size at least k such that groups are as homogeneous as possible.Then the records'attribute values in the same group are replaced by the group's centroid.Microaggregation algorithms'core ideas,the state-of-the-art and related techniques are surveyed.The existing algorithms are classified and analyzed.Evaluation methods of microaggregation algorithms are investigated.Finally,some open problems and the research directions in this area are discussed.