1. A computer implemented method of re-identification risk measurement of a dataset, the method comprising: retrieving the dataset comprising personally identifiable information for a plurality of individuals, each individual having cross-sectional (L1) data defining identifiable information and one or more entries of longitudinal (L2) data associated with the L1 data; reducing multiple occurrences for the same individual of the same L2 data to a single feature with an addition of a count; grouping individuals in L1 equivalence classes based on L1 data quasi-identifiers; ordering the features from most to least identifying within each L1 equivalence class; subsampling multiple features for each individual; determining a similarity measure by counting the individuals in the L1 equivalence class who's features comprise a superset of the subsampled features for the current individual; combining multiple similarity measures into a single measure per individual; and determining an overall risk measurement from the combined similarity measures.