Zhai, Xiaojun and Ait Si Ali, Amine and Amira, Abbes and Bensaali, Faycal (2017) ECG encryption and identification based security solution on the Zynq SoC for connected health systems. Journal of Parallel and Distributed Computing, 106. pp. 143-152. DOI https://doi.org/10.1016/j.jpdc.2016.12.016
Zhai, Xiaojun and Ait Si Ali, Amine and Amira, Abbes and Bensaali, Faycal (2017) ECG encryption and identification based security solution on the Zynq SoC for connected health systems. Journal of Parallel and Distributed Computing, 106. pp. 143-152. DOI https://doi.org/10.1016/j.jpdc.2016.12.016
Zhai, Xiaojun and Ait Si Ali, Amine and Amira, Abbes and Bensaali, Faycal (2017) ECG encryption and identification based security solution on the Zynq SoC for connected health systems. Journal of Parallel and Distributed Computing, 106. pp. 143-152. DOI https://doi.org/10.1016/j.jpdc.2016.12.016
Abstract
Connected health is a technology that associates medical devices, security devices and communication technologies. It enables patients to be monitored and treated remotely from their home. Patients’ data and medical records within a connected health system should be securely stored and transmitted for further analysis and diagnosis. This paper presents a set of security solutions that can be deployed in a connected health environment, which includes the advanced encryption standard (AES) algorithm and electrocardiogram (ECG) identification system. Efficient System-on-Chip (SoC) implementations for the proposed algorithms have been carried out on the Xilinx ZC702 prototyping board. The Achieved hardware implementation results have shown that the proposed AES and ECG identification based system met the real-time requirements and outperformed existing field programmable gate array (FPGA)-based systems in different key performance metrics such as processing time, hardware resources and power consumption. The proposed systems can process an ECG sample in 10.71ms and uses only 30% of the available hardware resources with a power consumption of 107mW.
Item Type: | Article |
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Uncontrolled Keywords: | Advanced encryption standard (AES); Electrocardiogram (ECG) encryption and identification; Field programmable gate array (FPGA); Zynq7 system on chip (SoC) |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > R Medicine (General) |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 24 Sep 2018 09:10 |
Last Modified: | 30 Oct 2024 17:27 |
URI: | http://repository.essex.ac.uk/id/eprint/23087 |