A New Watermarking System Based on Discrete Cosine Transform (DCT) in Color Biometric Images

Doğan, Şengül; Tuncer, Türker; Avcı, Engin; Gülten, Arif

doi:10.1007/s10916-011-9705-2

Cited by 10 publications

(1 citation statement)

References 25 publications

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“…Data-hiding methods, i.e., ECG steganography approaches, have been applied to ECG signals for securing patient information [14][15][16][17][18][19][20][21][22][23][24][25][26]. To protect against manipulations, researchers have presented schemes for digital watermarking of ECG signals [27][28][29][30][31]. To preserve the originality of the host ECG signal, the use of reversible ECG steganography based on wavelet transform has been suggested [32,33].…”

Section: Steganography Methodsmentioning

confidence: 99%

Diagnosis-Steganography-Transmission: An Innovative Integrated Paradigm for ECG Healthcare

2021

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The developing prominence of edge computing and Internet of Things-based wearables coupled with body sensors offer us a unique idea of integrating the Diagnosis, Steganography, and Transmission tasks in the healthcare domain. In this paper, we present an innovative Diagnosis-Steganography-Transmission architecture for health monitoring and real-time diagnosis especially designed for Coronary Artery Disease diagnostic purposes. The architecture works by extracting the patient's health state by a real-time execution of a preliminary diagnostic algorithm in the local embedded computing platform before the ECG data are transmitted over wireless networks for further analysis. Local pre-diagnosis assists the operation of the communication module in deciding when and how much data should be transmitted and the given quality. The novelty of the proposed work is that the integration of diagnosis, steganography, and communication tasks in a unified platform, because unequal importance of physiological signals (e.g., ECG) feature offers computing distribution of diagnosis, UEP-based steganography, and UEP-based transmission are inherently connected with each other. Using the proposed framework, the steganography embedder, source encoder, and channel encoder in the communication module effectively reconfigure the intricacy of the control factors to match the energy constraints while maintaining the reconstruction quality of the medical signal. Moreover, the diagnosis module also reconfigures the complexity of the process of diagnosis to match the communication bandwidth constraints. By deep CNN-based ECG classification for local pre-diagnosis, an immense heap of energy-saving is created by a huge diminishing in the transmission overhead (up to 99.3% in typical application set-up) as compared to always-on communication.

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Section: Steganography Methodsmentioning

confidence: 99%

Diagnosis-Steganography-Transmission: An Innovative Integrated Paradigm for ECG Healthcare

2021

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Discrete Wavelet Transform and Singular Value Decomposition Based ECG Steganography for Secured Patient Information Transmission

2014

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ECG Steganography provides secured transmission of secret information such as patient personal information through ECG signals. This paper proposes an approach that uses discrete wavelet transform to decompose signals and singular value decomposition (SVD) to embed the secret information into the decomposed ECG signal. The novelty of the proposed method is to embed the watermark using SVD into the two dimensional (2D) ECG image. The embedding of secret information in a selected sub band of the decomposed ECG is achieved by replacing the singular values of the decomposed cover image by the singular values of the secret data. The performance assessment of the proposed approach allows understanding the suitable sub-band to hide secret data and the signal degradation that will affect diagnosability. Performance is measured using metrics like Kullback-Leibler divergence (KL), percentage residual difference (PRD), peak signal to noise ratio (PSNR) and bit error rate (BER). A dynamic location selection approach for embedding the singular values is also discussed. The proposed approach is demonstrated on a MIT-BIH database and the observations validate that HH is the ideal sub-band to hide data. It is also observed that the signal degradation (less than 0.6%) is very less in the proposed approach even with the secret data being as large as the sub band size. So, it does not affect the diagnosability and is reliable to transmit patient information.

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Effective Electrocardiogram Steganography Based on Coefficient Alignment

Yang

Wang

2015

J Med Syst

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This study presents two types of data hiding methods based on coefficient alignment for electrocardiogram (ECG) signals, namely, lossy and reversible ECG steganographys. The lossy method is divided into high-quality and high-capacity ECG steganography, both of which are capable of hiding confidential patient data in ECG signals. The reversible data hiding method can not only hide secret messages but also completely restore the original ECG signal after bit extraction. Simulations confirmed that the perceived quality generated by the lossy ECG steganography methods was good, while hiding capacity was acceptable. In addition, these methods have a certain degree of robustness, which is rare in conventional ECG stegangraphy schemes. Moreover, the proposed reversible ECG steganography method can not only successfully extract hidden messages but also completely recover the original ECG data.

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A New Watermarking System Based on Discrete Cosine Transform (DCT) in Color Biometric Images

Cited by 10 publications

References 25 publications

Diagnosis-Steganography-Transmission: An Innovative Integrated Paradigm for ECG Healthcare

Diagnosis-Steganography-Transmission: An Innovative Integrated Paradigm for ECG Healthcare

Discrete Wavelet Transform and Singular Value Decomposition Based ECG Steganography for Secured Patient Information Transmission

Effective Electrocardiogram Steganography Based on Coefficient Alignment

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