Intelligent Data Aggregation and Merging Algorithms for Secured Storage of Medical Information in Cloud

Abstract

Data aggregation is playing major role in cloud environment for providing data security in terms of effective storage. Secure storage is a crucial task when stored the confidential data such as medical reports, official secrets and organization resources on cloud. This is time to propose a new technique for secured storage. For that purpose, we propose a new secured storage model using cryptography. This model uses a newly proposed data aggregation algorithm for forming effective group and a new data partitioning method for extracting the useful data which are grouped securely. Finally, a new data merging algorithm for segregating the original data which are partitioned in this model. The proposed model is useful for securing confidential medical data and also for making effective decisions over the diseases by medical expert systems. Experiments have been conducted in this research work for evaluating the efficiency of the proposed secured storage model by using UCI Repository medical datasets.