TY - JOUR
T1 - ECG encryption and identification based security solution on the Zynq SoC for connected health systems
AU - Zhai, Xiaojun
AU - Ait Si ali, Amine
AU - Amira, Abbes
AU - Bensaali, Faycal
PY - 2017/8/31
Y1 - 2017/8/31
N2 - 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.
AB - 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.
KW - Advanced encryption standard (AES)
KW - Electrocardiogram (ECG)
KW - encryption and identification
KW - Field programmable gate array (FPGA)
KW - Zynq7 system on chip (SoC)
U2 - 10.1016/j.jpdc.2016.12.016
DO - 10.1016/j.jpdc.2016.12.016
M3 - Article
VL - 106
SP - 143
EP - 152
JO - Journal of Parallel and Distributed Computing
JF - Journal of Parallel and Distributed Computing
SN - 0743-7315
ER -