An efficient quasi-identifier index based approach for privacy preservation over incremental data sets on cloud

► We investigate the efficiency of privacy preservation over large-scale incremental data sets on cloud. ► A distributed quasi-identifier index structure is proposed to efficiently update anonymous incremental data sets. ► Locality-sensitive hash function is used to place similar quasi-identifier groups on the same node to improve efficiency. ► We elaborate the process of generalization or specialization when data updates occur.