The invention discloses a
Skyline-based data generalization method. The method comprises the steps of
processing a data table according to a
data release privacy protection standard 10-
anonymity to obtain a re-identified risk quantity R of a policy, recording the risk quantity R as a threshold T, and determining a policy space {S,(R,U)} according to a value domain of a quasi-identifier attribute and the threshold T, wherein an R value of the policy comprised in the policy space {S,(R,U)} is not greater than the threshold T; filtering the policy space {S,(R,U)} by adopting epsilon-approximate
Skyline to obtain candidate policy spaces {G,(R,U)}; and performing
Skyline calculation on the candidate policy space {G,(R,U)} to obtain a recommended policy space {F,(R,U)}, wherein the recommended policy space {F,(R,U)} is a private policy space recommended for the data table. According to the method, the accuracy of
privacy protection policy recommendation is improved through an enumeration full policy space; the coverage range of an RU space is wide; multilevel demands of a user are met; the threshold T is set and the
privacy protection policies not meeting the requirements are filtered, so that the policy space
generation time is shortened; and the filtering is performed by adopting the epsilon-approximate Skyline, so that the scale of the candidate policy spaces is further reduced.