Hash Edward Curve Signcryption for Secure Big Data Transmission

Medical health service data is kept in huge dataset and shared through different devices. However, privacy and security of data sharing area significant concern, since data needs to be accessed from various locations in the distributed system. Therefore, a novel method called Hash Edward Curve Signcryption (HECS) is introduced for healthcare data communication in a secure manner. In the HECS method, related medical health service data is collected from the huge healthcare dataset. The proposed HECS method includes two major processes. First, Theil-Sen Robust Linear Regression is carried out to classifying the data and categorizes the data into number of classes. After the classification, the Hash Edward signcryption cryptographic technique is employed to perform the secured data transmission. In the designed cryptosystem, Pseudo ephemeral agreement key pair generation is performed for each session of data transmission. Then the HECS method performs the signcryption process for converting the data point into the encrypted data and generates the digital signature. Then in unsigncryption, the signature verification is carried out to check the user authenticity. This, in turn, secured data transmission is carried out with higher confidentiality. The assessment of the HESC method is carried with accuracy on classification and integrity of data. The quantitatively analysed results confirmed that the HECS method increases security than the orthodox methodology by means of improved data confidentiality rate and integrity rate.