Combining Fog Computing and Blockchain Based on the Internet of Medical Things to Preserve Patient Information Privacy
Mishall Al-Zubaidie, Rasha Halim Razzaq · Advances in computational intelligence and robotics book series · 2025
This chapter proposes an encrypted internet of medical of things (IoMT) privacy system (EIPS). To create strong security measures, the suggested EIPS uses the techniques of decision tree (DT), naive bayes (NB), twofish, and jellyfish inside private blockchain (PBC) and fog computing. Medical data is kept anonymous by using the twofish encryption technique. This study uses DT to make precise recommendations based on the gathered data, while NB is utilized to swiftly classify patient data. The jellyfish algorithm was employed in EIPS to improve data transmission security by identifying patterns in the data. The algorithms from twofish, NB, DT, and jellyfish are made to function well with PBC. Peer-to-peer data in IoMT is distributed and managed via EIPS. Fog computing (FC) has the advantage of accelerating decision-making without requiring the user to go to far-off clouds. The authors examined the security and performance of our system. The findings show that EIPS can handle extensive security measures with lightweight operations, making it suitable for use by health organizations.