A privacy protection algorithm based on hierarchical multiple sensitive attributes allowed by least mean square criterion
Tao Cui, Jijia Yang, Nan Meng, Wei Xie · 2016
Based on L-diversity multiple sensitive modules, a hierarchical multiple sensitive attributes algorithm is proposed according to least mean square criterion ---L-LMSU (L-Least Mean Square Uniqueness).The algorithm makes a hierarchical strategy according to the frequencies of the whole attributes firstly.Beyond the hierarchical strategy, the algorithm could decrease the hidden loss because of non-uniform distribution of attributes when releasing privacy data in groups.Analysis and experiments show that L-LMSU is with linear time complexity and could improve the availability of released privacy data and time performances effectively.