Medical Data Privacy Representation with Improved Encryption Algorithm - Sultana, Zaheer; Kumar , Deepak (International Journal of Intelligent Systems and Applications in Engineering, 2023)
For research projects involving health care, it might be necessary to collect patient health records from several locations, with various rules governing the release of personal health data. Due to the sensitive nature of health information; privacy is a major concern when patients’ health care records are used for dissertation. Data preservation is a technique for defending the integrity and confidentiality of data. Huge databases may contain metadata—uncertain, unstable elements—in their data that may include sensitive information, user profiles, and other information that is subject to intrusion from outside parties like hackers or attackers. They may abuse the information, which would compromise its privacy and confidentiality. The data must be stored safely and made accessible for future use. In order to preserve and safeguard people’s data privacy in terms of secrecy and dependability, an effective approach is required. In this paper, for encryption a new Advanced Twofish Encryption standard (ATFES) algorithm is proposed that helps to encrypt the collected raw data. Then, in order to generate the optimal key for encryption and decryption Optimized Radial Basis Function Networks (RBFNs) leveraged with Mayfly-Levy optimization algorithm (MLOA). This encrypted data will be stored in the cloud, and it will be transmitted via the blocks of the blockchain. The same ideal code that was used for encryption will be utilised to recover the encrypted data at the receiving end. The receiver is unable to get the data if the same key is not utilised. The research shows that the suggested techniques are more effective at encrypting and decrypting data over the other state-of-the-art methods. The Matlab platform is used to carry out the implementation.