ANAF-IoMT: A Novel Architectural Framework for IoMT-Enabled Smart Healthcare System by Enhancing Security Based on RECC-VC

The Internet of Medical Things (IoMT) is an arising trend that provides a significant amount of efficient and effective services for patients as well as healthcare professionals for the treatment of disparate diseases. The IoMT has numerous benefits; however, the security issue still persists as a challenge. The lack of security awareness among novice IoMT users and the risk of several intermediary attacks for accessing health information severely endanger the use of IoMT. In this article, rooted elliptic curve cryptography with Vigenere cipher (RECC-VC) centered security amelioration on the IoMT is proposed for enhancing security. First, this work utilizes the exponential K-anonymity algorithm for privacy preservation. Second, a new improved Elman neural network (IENN) is proposed for analyzing the sensitivity level of data. The Gaussian mutated chimp optimization is employed for weight updating in this IENN. Finally, a novel RECC-VC is proposed for securely uploading the data to the cloud server. Additionally, data are stored in the cloud server using blockchain technology. In experimental analysis, the proposed methodologies attain better results than the prevailing methods. The proposed IENN model achieves an accuracy of 96% and is validated against state-of-the-art methods. Also, the proposed RECC-VC attains 98% of the security level.

Automated summary

This article investigates how to enhance the security of the Internet of Medical Things using elliptic curve cryptography and Vigenere cipher, improving data security and privacy through algorithms for privacy preservation, neural networks, optimization methods, and blockchain technology.