期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 17, 期 3, 页码 1948-1957出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2020.2995228
关键词
Servers; Medical diagnostic imaging; Data aggregation; Monitoring; Encryption; COVID-19; data aggregation; e-healthcare; fog-based healthcare; privacy-preserving; wireless body area network (WBAN)
类别
资金
- National Science Foundation of China [61871064, 61501080, 61771090, 61601214]
- Fundamental Research Funds for the Central Universities [DUT19JC08]
- Guangxi Key Laboratory of Trusted Software [kx201903]
- Cloud Technology Endowed Professorship
Wearable body area network plays an important role in the current COVID-19 pandemic. The designed improved symmetric homomorphic cryptosystem and fog-based communication architecture support real-time data processing and monitoring, facilitating decision-making process based on real-time data analysis.
Wearable body area network is a key component of the modern-day e-healthcare system (e.g., telemedicine), particularly as the number and types of wearable medical monitoring systems increase. The importance of such systems is reinforced in the current COVID-19 pandemic. In addition to the need for a secure collection of medical data, there is also a need to process data in real-time. In this article, we design an improved symmetric homomorphic cryptosystem and a fog-based communication architecture to support delay- or time-sensitive monitoring and other-related applications. Specifically, medical data can be analyzed at the fog servers in a secure manner. This will facilitate decision making, for example, allowing relevant stakeholders to detect and respond to emergency situations, based on real-time data analysis. We present two attack games to demonstrate that our approach is secure (i.e., chosen-plaintext attack resilience under the computational Diffie-Hellman assumption), and evaluate the complexity of its computations. A comparative summary of its performance and three other related approaches suggests that our approach enables privacy-assured medical data aggregation, and the simulation experiments using Microsoft Azure further demonstrate the utility of our scheme.
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