A SURVEY ON PRIVACY PRESERVING TECHNIQUE USING K - NEAREST NEIGHBOR CLASSIFICATION

Data mining is a powerful new technique to discover knowledge within the large amount of the data. Also data mining is the process of discovering meaningful new relationship, patterns and trends by passing large amounts of data stored in corpus, using pattern recognition technologies as well as statistical and mathematical techniques. To protect user privacy, various privacy - preserving classification techniques have been proposed over the past decade. The existing techniques are not applicable to outsourced database envir onments where the data resides in encrypted form on a third - party server. This paper proposed a novel privacy - preserving k - NN classification protocol over encrypted data in the cloud. Our protocol protects the confidentiality of the data, user’s input quer y, and hides the data access patterns. We also evaluated the performance of our protocol under different parameter settings