Optimizing Wavelet ECG Watermarking to Maintain Measurement Performance According to Industrial Standard

Świerkosz, Agnieszka; Augustyniak, Piotr

doi:10.3390/s18103401

Cited by 13 publications

(9 citation statements)

References 29 publications

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“…In [11], Swierkosz and Augustyniak presented a mechanism, which uses optimized DWT to embed watermark bits into ECG signals. This method embeds watermark bits into the time-frequency ECG representation.…”

Section: A Data Hiding Methods Developed For Ecg Signalsmentioning

confidence: 99%

Robust Patient Information Embedding and Retrieval Mechanism for ECG Signals

et al. 2020

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At present, a patient's demography, such as name, age, and gender are stored separately from the acquired electrocardiogram (ECG) signal. This multiple storage mechanisms can create a severe threat to the reliability of diagnostics if the link between the demography data and the ECG signal breaks, either intentionally or unintentionally. This issue has become more prominent in recent years due to the use of a large number of wearable devices for physiological signal collection, especially in remote or nonclinical settings. In order to address this problem, in this paper, we propose a novel mechanism to embed patient's information within an ECG signal without degrading the accuracy of the physiological information contained in the ECG signal. In this work, a methodology is presented to find the less-significant region of the ECG signal. Then, the patient information is hidden in this region by modifying the selected discrete cosine transform (DCT) coefficients of the signal using our proposed embedding and decoding algorithms. Moreover, the patient information hidden in the ECG signal is able to resist filtering attack, such as high-pass filtering, which generally occur with the ECG signal processing. This is achieved via the use of error buffers in the embedding algorithm. The proposed mechanism can extract the embedded patient information, either in the presence or without the filtering attack. Moreover, a specifically designed synchronization sequence is added to identify the patient data embedded regions of the ECG signal at the decoding end. Further, as a security measure, the embedded patient details are scrambled using a secret key to protect the privacy of the patient. Our evaluation demonstrates the usefulness of the proposed methodology in successfully embedding the patient information without distorting the important medical information in an ECG signal. INDEX TERMS ECG signal, information hiding, watermarking, physiological signal processing, discrete cosine transform.

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Section: A Data Hiding Methods Developed For Ecg Signalsmentioning

confidence: 99%

Robust Patient Information Embedding and Retrieval Mechanism for ECG Signals

et al. 2020

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“…This method ensures higher embedding capacity and better security since the marked ECG signal is in decoded form. Swierkosz and Augustyniak have proposed an irreversible watermarking technique for ECG signal [ 47 ]. Forward wavelet transform is used to decompose the cover ECG signal and create the data container, followed by replacing intrinsic noises of the signal with the diagnosis data.…”

Section: Related Workmentioning

confidence: 99%

Bio-signal data sharing security through watermarking: a technical survey

2021

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Section: Introductionmentioning

confidence: 99%

“…Recently, several research works have developed data hiding methods [9][10][11][12][13][14][15][16][17][18][19] for the protection (or privacy) of sensitive information in ECG signals. ´Swierkosz and Augustyniak [9] proposed an ECG watermarking scheme based on the discrete wavelet transform (DWT) domain. With the use of a continuous noise measurement and adaptive coding bit depth, the watermarked ECGs generated by the approach were capable of resisting noise attacks.…”

Section: Introductionmentioning

confidence: 99%

An Improved ECG Steganography Using Integer Wavelet Transform and Offset Coefficient with LSB Substitution

Yang

Wang

2021

Preprint

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In this work, we present an improved steganography for electrocardiogram (ECG) hosts to solve the issues of existing ECG steganographic methods, which have less hiding capacity and insufficient signal-to-noise ratio (SNR)/ peak SNR (PSNR). Based on the integer wavelet transform (IWT) domain, sensitive (or private) data such as patients’ data and personal information can be efficiently embedded in an ECG host via the IWT coefficient adjustment and the least significant bit (LSB) technique. Simulations confirmed that the SNR/ PSNR, and payload of the proposed method outperform those of existing techniques. In addition, the proposed method is capable of resisting attacks, such as cropping, Gaussian noise-addition inversion, scaling, translation, and truncation attacks from third parties (or adversaries). Due to the fast computation time, the proposed method can be employed in portable biometric devices or wearable electronics.

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Optimizing Wavelet ECG Watermarking to Maintain Measurement Performance According to Industrial Standard

Cited by 13 publications

References 29 publications

Robust Patient Information Embedding and Retrieval Mechanism for ECG Signals

Robust Patient Information Embedding and Retrieval Mechanism for ECG Signals

Bio-signal data sharing security through watermarking: a technical survey

An Improved ECG Steganography Using Integer Wavelet Transform and Offset Coefficient with LSB Substitution

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