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.