The present invention includes a rotation based transformation method for preserving data privacy. A rotation based transformation method according to an embodiment of the present invention divides a given data set into a plurality of data subsets, applies a plurality of different rotation matrixes to the plurality of divided data subsets, respectively, to rotate the plurality of data subsets, and re-concatenates the plurality of rotated data subsets to generate a rotated data set. The rotated data set is released and used for data clustering. The rotation based transformation method is effectively used when the impact of the AK-ICA attack is mitigated. Meanwhile, when the two parties are related to the present invention, the two parties need to agree on parameters, such as the number of data subsets. It is preferable that the data subsets be divided into equal sizes. Further, rotation-unification work that removes relative rotation deviation between the plurality of different rotation matrices can be performed in order to provide valid clustering between the data subsets rotated using the different rotation matrixes.