Development of Modified ECC-Based Secured FoG-Assisted Healthcare Data Management System in IoT-Enabled WSN

Abstract

The Internet of Things (IoT) consists of a massive count of connected devices with different sensing support, particularly in medical health constraints sensing. In these summaries, secure communication and data collection to centralized servers is rather difficult for preventing the occurrence of diverse attacks for illegal data access. To tackle these problems, this task plans to design and implement the FoG-based secure data management system in IoT-WSN using adaptive encryption and decryption processes. As the FoG server is away from the corresponding aggregator node, it is transmitted via the other nodes using the proposed modified Elliptic Curve Cryptography (ECC)-based encryption process. For secured data transmission the designed method undergoes two main stages as message receiving stage, and the message-extraction stage. The hybridized meta-heuristic algorithm termed Jaya-Galactic Swarm Optimization (J-GSO) is used for modifying the ECC with an optimized key. From the simulation findings, the performance of the suggested scheme at the data size of three bytes is 3.08%, 3.22%, 3.65%, and 3.33% better than the MFO-m-ECC, PSO-m-ECC, GSO-m-ECC, and JA-m-ECC at the ECC curve variation of “secp192r1”. Experimental results reveal the superiority of the designed method when tested with baseline schemes regarding time complexity, space complexity, and cost function.