UPM Institutional Repository

Secured electrocardiograph (ECG) signal using fully homomorphic encryption technique


Citation

Shaikh, Muhammad Umair and Ahmad, Siti Anom and Wan Adnan, Wan Azizun (2020) Secured electrocardiograph (ECG) signal using fully homomorphic encryption technique. Test Engineering and Management, 82. 12029 - 12034. ISSN 0193-4120

Abstract

Digital signal processing and data analysis frequently utilized strategies in biomedical engineering research. This proposed study describes the steps of digital signal processing on electrocardiogram (ECG) and the security of the ECG signal by using Fully Homomorphic Encryption (FHE). Sharing the patient’s information through the Internet of Thing (IoT) for faster diagnosis has security and privacy issues. The present situation demands extremely secured details of patients. Consequently, securing the patient's information from ransomware is the main challenge in the healthcare industry. Development of secured ECG signal is essential to protect patients’ confidentially and to prevent mistreatment. The proposed encryption scheme FHE is performed on the encrypted ECG data where FHE can be applied in any system by using a various public key algorithm. The secured ECG transmission system will work on the fourth industrial revolution with four major themes: speed of care, ability to manage illness, the role of patient and the relationship between healthcare and service provider. Secure ECG signal provides innovation in multiple healthcare sectors such as medical research, patient care and hospital database. For the digital signal processing on ECG, QRS complex method will be used to display heart rate (HR) because it is the most visually obvious part of the ECG tracing and it is easy to encrypt the visual part in ECG tracing. This study demonstrates the implementation of FHE techniques that is Gentry algorithms in securing ECG signal transmission.


Download File

Full text not available from this repository.

Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
Publisher: The Mattingley Publishing
Keywords: Signal analysis; Electrocardiograph; Gentry encryption technique
Depositing User: Mohamad Jefri Mohamed Fauzi
Date Deposited: 23 Nov 2022 02:39
Last Modified: 23 Nov 2022 02:39
URI: http://psasir.upm.edu.my/id/eprint/87544
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item