Confidential and Efficient Query Services in the Cloud with Random Space Privacy Preserving Data

Abstract

Now a day’s cloud computing infrastructures are popularly used by peoples. Because of that cloud user can save their time as well as cost by using query services in cloud environment. In cloud, data owner upload their data in cloud and cloud user access that data. But sometime owner of data does not move to cloud or does not put their data in cloud because they not sure that this data is secure. Because some malicious users are present in cloud and they hack the data. So until cloud provider does not give the guaranteed of confidentiality and privacy of query, data owner does not move to cloud. So to increase the efficiency of query processing and save workload of processing of query, it is required to user to provide secure query services. The main purpose of using Random Space Perturbation approach is to provide confidentiality and efficient range query. RASP is combination of OPE, dimensionality expansion and random projection. To process range query to kNN query here kNN-R algorithm is used. It also used to increase the working process of query.