PMHE:A Wearable Medical Sensor Assisted Framework For Health Care Based On Blockchain And Privacy Computing

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 protection 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 use fully homomorphic encryption method to design a disease prediction model, which was implemented using 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 it avoids privacy and security issues caused by platform data leakage. 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.

Privacy Data Security Policy of Medical Cloud Platform Based on Lightweight Algorithm Model

The deterioration of aging population has seriously hindered the development of society. Medical cloud platform has been widely used to alleviate the pressure of aging population on social economy. Most of them collect the user’s sign information through the edge node and complete the disease prediction and diagnosis function combined with the cloud platform. However, the limited resources prevent the edge node from deploying the corresponding security policy after completing the data collection, storage, and calculation, which makes the edge data easy to be stolen. This paper proposes a security architecture of medical cloud platform based on lightweight algorithm model, which not only satisfies the needs of medical cloud platform to complete disease prediction and diagnosis accurately, but also creates a more secure edge node environment combined with other security strategies and hardware design. Finally, the prediction of cerebrovascular disease is used to verify the effectiveness of the proposed algorithm model.