An efficient Query Services in the Cloud Using kNN-R and RASP Data Perturbation

Abstract

Now a day’s cloud is more popular because in cloud users host the data and upload a large contained data. It has large databases to database service providers so database service providers maintain the services of range query services. In clouding process some users have a sensitive private data in that situation users can’t move the data for hosting until we provide security, confidentiality, perfectness, query privacy are guaranteed to the hosted data. We propose this system is by using RASP approach to gain confidentiality and efficient range query and kNN query services for protected data in the cloud. Random Space Perturbation (RASP) is combination of many approaches such us random projection, dimensionality expansion and order preserving encryption (OPE). KNN-R algorithm is design to process range query to k-Nearest Neighbor (KNN) query and also these approaches are used to increase the working process of query by secure multidimensional range query processing. The kNN-R algorithm is intended to work with the RASP range query algorithm to process the kNN queries. We have thoroughly analyzed the attacks on information, data and queries under an absolutely characterized threat model and practical security assumptions.