Medical Data Security for Healthcare Applications Using Hybrid Lightweight Encryption and Swarm Optimization Algorithm

TLDR: The main goal is to encrypt the medical data (EEG signal) and send to end user by utilizing proposed HLE–SO method, which combines Paillier encryption and KATAN algorithm, which provides the lightweight features.

Abstract: In medical field, securing every patient’s record is main concern, ascribed to many fraudulent cases occurring in the health sector. The data of every individual must be engraved and sent into end-user without any issues. Mainly in the healthcare industry, where thoughts are often focused on saving someone’s life and rightly so, but securing access to interfaces and computer systems that store private data like medical records is also an essential factor to consider. Data security is a corresponding action between controlling access to information while allowing free and easy access to those who need that information. Still few problems are focused by the physician in the health sector. Patient’s data should be kept securely in medical provider servers so that physicians can provide proper treatments. To ensure secure storage and access management, we propose a novel hybrid lightweight encryption using swarm optimization algorithm (HLE–SO).The proposed HLE–SO technique merge Paillier encryption and KATAN algorithm, which provides the lightweight features. Generally, the lightweight encryption algorithms are affected by the key space. We introduce the swarm optimization algorithm to optimize the key space by changing the number of iteration round. Our main goal is to encrypt the medical data (EEG signal) and send to end user by utilizing proposed HLE–SO method. Finally, the implementation is done with MATLAB tool with different EEG signal data set. The simulation results of proposed HLE–SO technique is compared with the existing state-of-art techniques in terms of different performance metrics are MSE, PSNR, SSIM, PRD, encryption time and decryption time.