Integrity and memory consumption aware electronic health record handling in cloud

Cloud environment greatly necessitates two key factors namely integrity and memory consumption. In the proposed work, an efficient integrity check system (EICS) is presented for electronic health record (EHR) classification. The existing system does not concentrate on storage concerns such as storing and retrieving files in cloud and memory storage overheads. De-duplication is one of the solution, however original information loss might take place. This is mitigated by the suggested research work namely Integrity and Memory Consumption aware De-duplication Method (IMCDM), where health care files are stored in secured and reliable manner. File Indexed table are created for all the files for enhancing de-duplication performance before uploading it into server. Duplication existence can be obtained from the indexing table which comprises of file features and hash values. Support vector machine (SVM) classifier is used in indexing table construction for file feature learning. Labels allotted through SVM classifier is considered as index values. Two level encryption is used followed by indexing construction, and stored in cloud severs. For avoiding redundant data, a decrypted hash index comparison is performed with previously stored contents. Various security key based on individual user’s generation is carried for ensuring security and XOR operation is performed with received encrypted file. The evaluation is performed using the Java simulation tool, which aids in validating the proposed methodology against existing research.