The e-Health care system is a system that stores the patient’s personal health record online with privacy. Ensuring the protection and secrecy of patient information in the cloud is a very significant one; security increases trust. To enhance the storage privacy in cloud, an innovative and effective model is presented. In the projected work, two medical datasets are considered for the analysis of a patient’s information security in the cloud. Initially, the medical dataset is clustered in the formation of different groups in order to various diseases using K-Medoid Clustering (KMC) depends on the Euclidian distance. To enhance the security for clustered data, it is secured in the cloud by means of itemset mining algorithm called Preserving Maximum Utility Itemset Mining (PMUIM). With the intention of attaining high data security, the optimal threshold value in PMUIM is chosen by Modified Whale Optimization (MWO). The simulation result demonstrates that the proposed KMC-MWO algorithm improves the accuracy of e-Health care data privacy in all the datasets and it achieves less execution time compared to existing algorithms.
Volume 12 | Issue 1
Pages: 317-328
DOI: 10.5373/JARDCS/V12I1/20201411