AFD and chaotic map‐based integrated approach for ECG compression, steganography and encryption in E‐healthcare paradigm

Abstract The proliferation of tele‐healthcare services at an accelerated rate raises concerns over the management,security and privacy of the patient's confidential data (an individual's personal details and medical biography) during its transmission and storage. To resolve these issues, a...

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Main Authors: Neetika Soni, Indu Saini, Butta Singh
Format: Article
Language:English
Published: Wiley 2021-07-01
Series:IET Signal Processing
Online Access:https://doi.org/10.1049/sil2.12031
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spelling doaj-32c2cd38be834bc2a1730f11ff5b27b82021-08-02T08:30:44ZengWileyIET Signal Processing1751-96751751-96832021-07-0115533735110.1049/sil2.12031AFD and chaotic map‐based integrated approach for ECG compression, steganography and encryption in E‐healthcare paradigmNeetika Soni0Indu Saini1Butta Singh2Department of Electronics and Communication Engineering Dr B R Ambedkar National Institute of Technology Jalandhar IndiaDepartment of Electronics and Communication Engineering Dr B R Ambedkar National Institute of Technology Jalandhar IndiaDepartment of Electronics and Communication Engineering Guru Nanak Dev University Regional Campus Jalandhar IndiaAbstract The proliferation of tele‐healthcare services at an accelerated rate raises concerns over the management,security and privacy of the patient's confidential data (an individual's personal details and medical biography) during its transmission and storage. To resolve these issues, amalgamation of three fundamental techniques of remote healthcare systems, that is, signal compression, data hiding and encryption, are proposed. The proposed approach applies the recently developed adaptive Fourier decomposition (AFD) technique to decompose the electrocardiogram signal in terms of adaptively selected basis functions from the orthogonal rational function that performs a high fidelity compression. Later, chaotic map‐based steganography and encryption are proposed on the AFD coefficients to secure the confidential information and the signal itself. The performance of the three processes is evaluated in terms of distortion (both statistical and clinical), compression [(compression ratio (CR) and quality score], steganography [embedding capacity (EC), bit error rate], and encryption (sensitivity, predictivity, correlation coefficient). By implementing on 48 records of Massachusetts Institute of Technology‐Beth Israel Hospital arrhythmia database and varying N from 15 to 120, the proposed work achieves average CR, EC, and percentage residual difference of 62.39–11.79, 7 × 10−3–6 × 10−2 and 3.77–0.32, respectively, with a highly linear relationship among them. The results explicitly display the competency of the proposed technique in comparison with the existing techniques that are available currently.https://doi.org/10.1049/sil2.12031
collection DOAJ
language English
format Article
sources DOAJ
author Neetika Soni
Indu Saini
Butta Singh
spellingShingle Neetika Soni
Indu Saini
Butta Singh
AFD and chaotic map‐based integrated approach for ECG compression, steganography and encryption in E‐healthcare paradigm
IET Signal Processing
author_facet Neetika Soni
Indu Saini
Butta Singh
author_sort Neetika Soni
title AFD and chaotic map‐based integrated approach for ECG compression, steganography and encryption in E‐healthcare paradigm
title_short AFD and chaotic map‐based integrated approach for ECG compression, steganography and encryption in E‐healthcare paradigm
title_full AFD and chaotic map‐based integrated approach for ECG compression, steganography and encryption in E‐healthcare paradigm
title_fullStr AFD and chaotic map‐based integrated approach for ECG compression, steganography and encryption in E‐healthcare paradigm
title_full_unstemmed AFD and chaotic map‐based integrated approach for ECG compression, steganography and encryption in E‐healthcare paradigm
title_sort afd and chaotic map‐based integrated approach for ecg compression, steganography and encryption in e‐healthcare paradigm
publisher Wiley
series IET Signal Processing
issn 1751-9675
1751-9683
publishDate 2021-07-01
description Abstract The proliferation of tele‐healthcare services at an accelerated rate raises concerns over the management,security and privacy of the patient's confidential data (an individual's personal details and medical biography) during its transmission and storage. To resolve these issues, amalgamation of three fundamental techniques of remote healthcare systems, that is, signal compression, data hiding and encryption, are proposed. The proposed approach applies the recently developed adaptive Fourier decomposition (AFD) technique to decompose the electrocardiogram signal in terms of adaptively selected basis functions from the orthogonal rational function that performs a high fidelity compression. Later, chaotic map‐based steganography and encryption are proposed on the AFD coefficients to secure the confidential information and the signal itself. The performance of the three processes is evaluated in terms of distortion (both statistical and clinical), compression [(compression ratio (CR) and quality score], steganography [embedding capacity (EC), bit error rate], and encryption (sensitivity, predictivity, correlation coefficient). By implementing on 48 records of Massachusetts Institute of Technology‐Beth Israel Hospital arrhythmia database and varying N from 15 to 120, the proposed work achieves average CR, EC, and percentage residual difference of 62.39–11.79, 7 × 10−3–6 × 10−2 and 3.77–0.32, respectively, with a highly linear relationship among them. The results explicitly display the competency of the proposed technique in comparison with the existing techniques that are available currently.
url https://doi.org/10.1049/sil2.12031
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