Multidimentional k-anonymity
K-anonymity is hard, besides the common mistakes (such as missing quasi-identifiers or using a too small value of k) [1] it is also an NP-hard problem to try and optimize data utility [2]. One of the ways to optimize utility and determine which combination of methods stays under the required threshold (e.g. no equivalence classes smaller than k) is to apply every combination of methods and determine which is best....