1. A risk evaluation method, for evaluating an anonymous dataset generated according to an original dataset, and comprising: acquiring a plurality of appearing times respectively corresponding to a plurality of original values of the original dataset; generating a partition set and a weight table according to a sample parameter, an anonymous parameter and the appearing times; dividing the original dataset into a plurality of data partitions according to the partition set, and generating a penetration dataset according to the weight table and the data partitions, wherein the penetration dataset comprises a plurality of sample data; comparing each sample data with a plurality of anonymous data of the anonymous dataset to obtain a plurality of matching quantities respectively corresponding to the sample data; and calculating and outputting a risk evaluation result according to the matching quantities.