The amount of computer-stored information is growing faster with each passing day. This growth and the way in which the stored data are accessed through a variety of channels have raised the alarm about the protection of the individual privacy of the respondents whose data are being collected and stored. On the one hand, data should be available to researchers and statistical agencies so that the necessary research and planning activities can be conducted. However, on the other hand, the right of respondents to privacy must be protected. Statistical disclosure control (SDC) is the discipline which cares about keeping a balance between data access and privacy protection. k-Anonymity is one particular approach to SDC for individual data (microdata): the record corresponding to a specific respondent is k-anonymous if an intruder can at best link the record to a group of k respondents containing the correct one. This paper surveys the use of a special clustering technique called microaggregation to provide k-anonymity.