FRORSS: Fast result object retrieval using similarity search on cloud

This paper involves a cloud computing environment in which the data owner out sources the similarity search service to a third party service provider. The user provides an example query to the server to retrieve similar data. Privacy of the outsourced data is important because they may be sensitive, valuable or confidential data. The data should be made available to the authorized client/client groups, but not to be revealed to the service provider in which the data is stored. Given this scenario, the paper presents a technique called FRORSS which has build phase, data transformation and search phase. The build phase is about uploading the data; the data transformation phase transforms the data before submitting it to the service provider for similarity queries on the transformed data; search phase involves searching similar object with respect to query object. Experiments have been carried out on real data sets which exhibits that the proposed work is capable of providing privacy and achieving accuracy at a lower value of result measure in comparision with FDH [1].