Abstract
The rapid development of Internet of Medical Things (IoMT) is remarkable. However, IoMT faces many problems including privacy disclosure, long delay of service orders, low retrieval efficiency of medical data, and high energy cost of fog computing. For these, this paper proposes a data privacy protection and efficient retrieval scheme for IoMT based on low-cost fog computing. First, a fog computing system is located between a cloud server and medical workers, for processing data retrieval requests of medical workers and orders for controlling medical devices. Simultaneously, it preprocesses physiological data of patients uploaded by IoMT, collates them into various data sets, and transmits them to medical institutions in this way. It makes the entire execution process of low latency and efficient. Second, multidimensional physiological data are of great value, and we use ciphertext retrieval to protect privacy of patient data in this paper. In addition, this paper uses range tree to build an index for storing physiological data vectors, and meanwhile a range retrieval method is also proposed to improve data search efficiency. Finally, bat algorithm (BA) is designed to allocate cost on a fog server group for significant energy cost reduction. Extensive experiments are conducted to demonstrate the efficiency of the proposed scheme.
Highlights
Until now, more than 150 million people worldwide have been suffering from COVID-19, resulting in more than 3 million deaths
It is important for them to use IoMT to manage, diagnose, and provide treatment advices to patients remotely. e medical devices or health detection sensors are connected with a computer which is connected to a cloud sever via a network
If the encrypted data are uploaded to a cloud server and the retrieval is not processed based on ciphertext, medical workers need to decrypt the ciphertext before retrieving it
Summary
More than 150 million people worldwide have been suffering from COVID-19, resulting in more than 3 million deaths. If the encrypted data are uploaded to a cloud server and the retrieval is not processed based on ciphertext, medical workers need to decrypt the ciphertext before retrieving it. The fog computing server sends decrypted data to medical workers for disease diagnosis and analysis. E second layer is a fog computing server group made up of multiple highperformance servers that process data and execute orders sent by the healthcare workers and the IoMT. (1) is paper proposes an IoMT retrieval service based on fog computing, which enables medical workers to efficiently obtain IoMT data. E fog computing system makes the data transmission of IoMT devices and the retrieval request of medical workers efficient with low latency. Simulation results show that the proposed scheme achieves high efficiency and accuracy, while significantly reducing energy cost.
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