Abstract
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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Ameen M, Liu J, Kwak K (2012) Security and privacy issues in wireless sensor networks for healthcare applications. J Med Syst 36(1):93–101. doi: 10.1007/s10916-010-9449-4
Act, A. (1996) Health insurance portability and accountability act of 1996. Public Law, 104, 191. doi:10.4135/9781452234243.n359
Sufi F, Khalil I (2009) A new feature detection mechanism and its application in secured ECG transmission with noise masking. J Med Syst 33(2):121–132. doi: 10.1007/s10916-008-9172-6
Cheddad A et al. (2010) Digital image steganography: Survey and analysis of current methods, Signal Process, 90(3):727–752. doi:10.1016/j.sigpro.2009.08.010
Hernandez J R, Amado M, Perez-Gonzalez F (2000) DCT-domain watermarking techniques for still images: Detector performance analysis and a new structure. IEEE Trans. Image Process. 9(1): 55–68. doi: 10.1109/83.817598
Dogan S, Tuncer T, Avci E, Gulten A (2012) A New Watermarking System Based on Discrete Cosine Transform in Color Biometric Images. J Med Syst 36(4):2379–2385. doi:10.1007/s10916-011-9705-2
Chin-Chen Chang, Piyu Tsai, Chia-Chen Lin (2005) SVD-based digital image watermarking scheme, Pattern Recognit. Lett. 26(10):1577–1586. doi:10.1016/j.patrec.2005.01.004
Gupta A K, Raval M S (2012) A robust and secure watermarking scheme based on singular values replacement. Sadhana 37(4):425–440. doi:10.1007/s12046-012-0089-x
Ganic E, Eskicioglu A M (2004) Robust DWT-SVD domain image watermarking: embedding data in all frequencies. Proceedings of the 2004 Multimedia and Security Workshop on Multimedia and Security - MM&Sec’04.166-174. doi:10.1145/1022431.1022461
Thabit R, Khoo B E (2014) Robust reversible watermarking scheme using Slantlet transform matrix. J Syst Software 88:74–86. doi:10.1016/j.jss.2013.09.033
Martins D, Guyennet H et al. (2010) Steganography in MAC Layers of 802.15.4 Protocol for Securing Wireless Sensor Networks. 2010 International Conference on Multimedia Information Networking and Security. 4(6):824–828. doi:10.1109/mines.2010.175
Zielińska E, Mazurczyk W, Szczypiorski K (2014) Trends in steganography. Commun ACM 57(3):86–95. doi:10.1145/2566590.2566610
Bhat K V, Sengupta I, Das A (2010) An adaptive audio watermarking based on the singular value decomposition in the wavelet domain. Digit Signal Process 20(6):1547–1558. doi:10.1016/j.dsp.2010.02.006
Natgunanathan I, Xiang Y, Rong Y, Peng D (2013) Robust patchwork-based watermarking method for stereo audio signals. Multimed Tools Appl 1–24. doi:10.1007/s11042-013-1454-4
Marvel L M, Boncelet C G, Retter C T (1999) Spread spectrum image steganography. IEEE Trans. Image Process. 8(8):1075–1083. doi:10.1109/83.777088
Zaidoon Kh. Al-Ani et al. (2010) Overview: Main fundamentals for steganography. Journal of Computing 2(3):158–165
Bender et al. (1996) Techniques for data hiding. IBM Syst. J. 35(3.4):313–336. doi:10.1147/sj.353.0313
Christian Cachin (2004) An information-theoretic model for steganography. Inform Comput 192(1):41–56. doi:10.1016/j.ic.2004.02.003
Liu J, Tang G, Sun Y (2013) A secure steganography for privacy protection in healthcare system. J Med Syst, 37(2). doi:10.1007/s10916-012-9918-z
Xuan Kong, Rui Feng (2001) Watermarking medical signals for telemedicine. IEEE T Inf Technol B 5(3):195–201. doi:10.1109/4233.945290
Chen S T, Guo Y J, Huang, H N, Kung W M, Tseng K K, Tu S Y (2014) Hiding Patients Confidential Data in the ECG Signal via a Transform-Domain Quantization Scheme. J Med Syst 38(6). doi:10.1007/s10916-014-0054-9
Engin M, Çidam O, Engin E Z (2005) Wavelet transformation based watermarking technique for human electrocardiogram (ECG). J Med Syst 29(6):589–594. doi:10.1007/s10916-005-6126-0
Nergui M, Acharya U S, Acharya U R, Yu W (2010) Reliable and Robust Transmission and Storage Techniques for Medical Images with Patient Information. J Med Syst 34(6):1129–1139. doi:10.1007/s10916-009-9332-3
Mehmet Engin, Oğuz Çıdam, Erkan Zeki Engin (2005) Wavelet Transformation Based Watermarking Technique for Human Electrocardiogram (ECG). J Med Syst 29(6):589–594. doi:10.1007/s10916-005-6126-0
Ibaida A, Khalil I (2013) Wavelet Based ECG Steganography for Protecting Patient Confidential Information in Point-of-Care Systems. IEEE Trans. Biomed. Eng. 60(12):3322–3330. doi:10.1109/tbme.2013.2264539
Tseng K K, He X, Kung W M, Chen S T, Liao M, Huang H N (2014) Wavelet-Based Watermarking and Compression for ECG Signals with Verification Evaluation. Sensors 14(2):3721–3736. doi:10.3390/s140203721
Kozat Suleyman S et al. (2009) Embedding and retrieving private metadata in electrocardiograms. J Med Syst 33(4):241–259. doi:10.1007/s10916-008-9185-1
Nayak J, Subbanna Bhat P, Acharya U R, Sathish Kumar M (2009) Efficient Storage and Transmission of Digital Fundus Images with Patient Information Using Reversible Watermarking Technique and Error Control Codes. J Med Syst 33(3):163–171. doi:10.1007/s10916-008-9176-2
Planitz B M, Maeder A J (2005) A study of block-based medical image watermarking using a perceptual similarity metric. DICTA’05. Proceedings Digital Image Computing: Techniques and Applications 2005. doi:10.1109/dicta.2005.1578168
Gonzalez R C, Woods R E (2002) Digital image processing. 2nd SL, Prentice Hall.
Shensa M J (1992) The discrete wavelet transform: wedding the a trous and Mallat algorithms. IEEE T Signal Proces 40(10):2464–2482. doi:10.1109/78.157290
Heil C E, Walnut D F (1989) Continuous and discrete wavelet transforms. SIAM Review 31(4):628–666. doi:10.1137/1031129
Henry E R, Hofrichter J (2010) Singular value decomposition: application to analysis of experimental data. Method ENZYMOL 210: 81–138. doi:10.1016/0076-6879(92)10010-b
Wall M E, Rechtsteiner A, Rocha L M (2003) Singular value decomposition and principal component analysis. A practical approach to microarray data analysis 91–109. doi:10.1007/0-306-47815-3_5
Moody G B, Mark R (1992) MIT-BIH arrhythmia database directory. MITBIH Database Distribution, Harvard–MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. http://www.physionet.org/physiobank/database/html/mitdbdir/mitdbdir.htm. Accessed 23 May 2014
Gari D. Clifford (2002) Signal Processing Methods for Heart Rate Variability. Dissertation, University of Oxford
Pan J, Tompkins W J (1985) A Real-Time QRS Detection Algorithm. IEEE Trans. Biomed. Eng. 32(3):230–236. doi:10.1109/tbme.1985.325532
Gari D. Clifford (2010) MIT website. www.mit.edu/%7Egari/CODE/ECGtools/ecgBag/. Accessed 23 May 2014
Sankur B (2002) Statistical evaluation of image quality measures. J. Electron. Imaging 11(2):206–223. doi:10.1117/1.1455011
Huynh-Thu Q, Ghanbari M (2008) Scope of validity of PSNR in image/video quality assessment. Electron Lett 44(13):800. doi:10.1049/el:20080522
Al-Fahoum (2006) Quality assessment of ECG compression techniques using a wavelet-based diagnostic measure. IEEE Trans. Inf. Technol. Biomed. 10(1):182–191. doi:10.1109/titb.2005.855554
Cihan Varol, Coskun Bayrak (2011) Estimation of quality of service in spelling correction using Kullback–Leibler divergence. Expert Syst. Appl. 38(5):6307–6312. doi:10.1016/j.eswa.2010.11.112
Sung-Hyuk Cha (2007) Comprehensive survey on distance/similarity measures between probability density functions. International Journal of Mathematical Models and Methods in Applied Sciences 1:300–307
Couceiro R, Carvalho P et al. (2008) Detection of Atrial Fibrillation using model-based ECG analysis. 2008 19th International Conference on Pattern Recognition. doi:10.1109/icpr.2008.4761755
Gacek, Adam, Witold, Pedrycz (2012) ECG Signal Processing, Classification and Interpretation. Springer
Oberkampf, Roy (2010) Verification and validation in scientific computing. Cambridge University Press, Cambridge
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Edward Jero, S., Ramu, P. & Ramakrishnan, S. Discrete Wavelet Transform and Singular Value Decomposition Based ECG Steganography for Secured Patient Information Transmission. J Med Syst 38, 132 (2014). https://doi.org/10.1007/s10916-014-0132-z
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DOI: https://doi.org/10.1007/s10916-014-0132-z