Efficient and Secure Privacy Analysis for Medical Big Data Using TDES and MKSVM with Access Control in Cloud.

Abstract

Big Data and cloud computing are two essential issues in the recent years, empowers computing resources to be given as Information Technology services with high efficiency and effectiveness. So as to protect the security of data holders, data are regularly stored in the cloud in an encrypted form. In any case, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for big data storage and processing in the cloud along with access control. In this paper dissected the medical big data security utilizing encryption with access control process. Big database reduce process Map-Reduce framework with Optimal Fuzzy C means (OFCM) to Clustered data are accumulated in the cloud and furthermore using classification approach to classify sensitive and non-sensitive data in the cloud to encryption. This security process Triple DES (TDES) to encrypted and stored in the cloud and propose practical optimization techniques that further enhance the scheme's performance, at long last authentication phase with attribute-based access control is used to authenticate data in cloud sim. From the proposed method the clustering, classification and encryption results are compared to existing approaches.