Journal of Cloud Computing: Advances, Systems and Applications (Dec 2022)

PMHE: a wearable medical sensor assisted framework for health care based on blockchain and privacy computing

  • Jindong Zhao,
  • Wenshuo Wang,
  • Dan Wang,
  • Xuan Wang,
  • Chunxiao Mu

DOI
https://doi.org/10.1186/s13677-022-00373-8
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 17

Abstract

Read online

Abstract Nowadays, smart medical cloud platforms have become a new direction in the industry. However, because the medical system involves personal physiological data, user privacy in data transmission and processing is also easy to leak in the smart medical cloud platform. This paper proposed a medical data privacy preserving framework named PMHE based on blockchain and fully homomorphic encryption technology. The framework receives personal physiological data from wearable devices on the client side, and uses blockchain as data storage to ensure that the data cannot be tampered with or forged; Besides, it uses fully homomorphic encryption method to design disease prediction models implemented by smart contracts. In PMHE, data is encoded and encrypted on the client side, and encrypted data is uploaded to the cloud platform via the public Internet, preventing privacy leakage caused by channel eavesdropping; smart contracts run on the blockchain platform for disease prediction, and the operators participating in computing are encrypted user data too. So, privacy and security issues caused by platform data leakage are avoided. The client-to-cloud interaction protocol is also designed to overcome the defect that fully homomorphic encryption only supports addition and multiplication by submitting tuples on the client side, to ensure that the prediction model can perform complex computing. In addition, the design of the smart contract is introduced in detail, and the performance of the system is analyzed. Finally, experiments are conducted to verify the operating effect of the system, ensuring that user privacy is not leaked without affecting the accuracy of the model, and realizing a smart medical cloud platform in which data can be used but cannot be borrowed.

Keywords