Secure and intelligent 5G-enabled remote patient monitoring using ANN and Choquet integral fuzzy VIKOR

Abstract

Rapid advancements in healthcare technologies necessitate efficient and secure remote patient monitoring systems. This research develops an intelligent system that combines ANN technology and 5G infrastructure with MCDM methods based on Choquet Integral Fuzzy VIKOR to improve medical data acquisition processes. Physical Layer Security (PLS) is a main emphasis point since it protects transmitted healthcare data from eavesdroppers and cyber intruders. The proposed model implements Reinforcement Learning with Hyper-parameter tuning and Lasso regression to obtain a 97.25% accuracy level, which exceeds Physical-Layer Authentication with Superimposed Independent authentication Tags PLA-SIT (97%), Flexible Physical Layer Authentication FPLA (96.8%) and Privacy-Embedded Lightweight and Efficient Automated PLA (95.3%). The proposed model surpasses both CNN-based mechanisms by 94.7%, Shamir’s Secret Sharing Algorithm by 90.7%, and the Blowfish Algorithm by 82.3%. The enhanced quality of service alongside reliability produces the model as a dependable solution for MIoT applications that will exist in the next generation.