Citation
Abstract
ECG signal differs from individual to individual, making it hard to be emulated and copied. In recent times ECG is being used for identifying the person. Hence, there is a requirement for a system that involves digital signal processing and signal security so that the saved data are secured at one place and an authentic person can see and use the ECG signal for further diagnosis. The study presents a set of security solutions that can be deployed in a connected healthcare territory, which includes the partially homomorphic encryption (PHE) techniques used to secure the electrocardiogram (ECG) signals. This is to record confidentially and prevent the information from meddling, imitating and replicating. First, Pan and Tompkins’s algorithm was applied to perform the ECG signal processing. Then, partially homomorphic encryption (PHE) technique - Rivest-Shamir-Adleman (RSA) algorithm was used to encrypt the ECG signal by using the public key. The PHE constitutes a gathering of semantically secure encryption works that permits certain arithmetical tasks on the plaintext to be performed straightforwardly on the ciphertext. The study shows a faster and 90% accurate result before and after encryption that indicates the lightweight and accuracy of the RSA algorithm. Secure ECG signal provides innovation in multiple healthcare sectors such as medical research, patient care and hospital database.
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Official URL or Download Paper: http://www.pertanika.upm.edu.my/pjst/browse/specia...
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Engineering Malaysian Research Institute on Ageing |
DOI Number: | https://doi.org/10.47836/pjst.28.S2.18 |
Publisher: | Universiti Putra Malaysia Press |
Keywords: | ECG signal; Arrhythmias detection; PHE technique–RSA algorithm |
Depositing User: | Ms. Nuraida Ibrahim |
Date Deposited: | 17 Aug 2021 21:49 |
Last Modified: | 17 Aug 2021 22:27 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.47836/pjst.28.S2.18 |
URI: | http://psasir.upm.edu.my/id/eprint/73390 |
Statistic Details: | View Download Statistic |
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