Double-layer data-hiding mechanism for ECG signals

Abstract Due to the advancement in biomedical technologies, to diagnose problems in people, a number of psychological signals are extracted from patients. We should be able to ensure that psychological signals are not altered by adversaries and it should be possible to relate a patient to his/her corresponding psychological signal. As far as our awareness extends, none of the existing methods possess the capability to both identify and verify the authenticity of the ECG signals. Consequently, this paper introduces an innovative dual-layer data-embedding approach for electrocardiogram (ECG) signals, aiming to achieve both signal identification and authenticity verification. Since file name-based signal identification is vulnerable to modifications, we propose a robust watermarking method which will embed patient-related details such as patient identification number, into the medically less-significant portion of the ECG signals. The proposed robust watermarking algorithm adds data into ECG signals such that the patient information hidden in an ECG signal can resist the filtering attack (such as high-pass filtering) and noise addition. This is achieved via the use of error buffers in the embedding algorithm. Further, modification-sensitive fragile watermarks are added to ECG signals. By extracting and checking the fragile watermark bits, we can determine whether an ECG signal is modified or not. To ensure the security of the proposed mechanism, two secret keys are used. Our evaluation demonstrates the usefulness of the proposed system.

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Publication Details

Journal
EURASIP Journal on Advances in Signal Processing
Published
2024-09-16
DOI
https://doi.org/10.1186/s13634-024-01180-w
Citations
5
Primary Topic
ECG Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
2.01
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article

Double-layer data-hiding mechanism for ECG signals

Chandan Karmakar, Iynkaran Natgunanathan, Tianrui Zong, Sutharshan Rajasegarar
5 citations
EURASIP Journal on Advances in Signal Processing
ECG Monitoring and Analysis
2.01
article

Double-layer data-hiding mechanism for ECG signals

Chandan Karmakar, Iynkaran Natgunanathan, Tianrui Zong, Sutharshan Rajasegarar
article en
5 citations

Abstract

Abstract Due to the advancement in biomedical technologies, to diagnose problems in people, a number of psychological signals are extracted from patients. We should be able to ensure that psychological signals are not altered by adversaries and it should be possible to relate a patient to his/her corresponding psychological signal. As far as our awareness extends, none of the existing methods possess the capability to both identify and verify the authenticity of the ECG signals. Consequently, this paper introduces an innovative dual-layer data-embedding approach for electrocardiogram (ECG) signals, aiming to achieve both signal identification and authenticity verification. Since file name-based signal identification is vulnerable to modifications, we propose a robust watermarking method which will embed patient-related details such as patient identification number, into the medically less-significant portion of the ECG signals. The proposed robust watermarking algorithm adds data into ECG signals such that the patient information hidden in an ECG signal can resist the filtering attack (such as high-pass filtering) and noise addition. This is achieved via the use of error buffers in the embedding algorithm. Further, modification-sensitive fragile watermarks are added to ECG signals. By extracting and checking the fragile watermark bits, we can determine whether an ECG signal is modified or not. To ensure the security of the proposed mechanism, two secret keys are used. Our evaluation demonstrates the usefulness of the proposed system.

EURASIP Journal on Advances in Signal ProcessingVol. 2024(1)
Deakin University (AU)
Openalex Percentile: Top 12%
ECG Monitoring and Analysis
2.01
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