Privacy Preserving Combinatorial Function for Multi-Partitioned Data Sets
To preserve the electronic fitness records of data mining applications, data perturbation is used. It is a form of privacy-preserving data mining. An improved amount and range of information stored in databases has direct to an enhancement in the desire for ranked and “Best match” queries. Such queries are mainly applicable when dealing with privacy-sensitive information. To facilitate privacy preservation in data mining or machine learning algorithms over horizontally partitioned or vertically partitioned data, many protocols have been proposed using SMC and various secure building blocks.