Advertisement

Curvelet Based ECG Steganography for Protection of Data

  • Vishakha PatilEmail author
  • Mangal Patil
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 28)

Abstract

A ECG steganography provides safe communication over internet such as transformation of patient information embed on ECG signals. The data hiding technique are used here in which steganography is hiding the patient information in image, video, audio and signal etc. The very important challenge to ECG steganography is extract data and signal without loss. İn this technique, we use the curvelet transform for evaluating coefficients, converts information into binary format by using quantization and adaptive LSB algorithm for embedding. The ECG signals for steganography are taken from database of MIT-BIH. From outcome we have observed that the signal loss is less after embedding when the coefficients near to zero. The overlapping of embed watermark is avoided by using sequence. The performance is observed by using parameter such as peak signal to noise ratio, percentage residual difference, correlation and time elapsed at embedding. The extraction performance is measured by using correlation, BER and time elapsed parameters. At extraction bit error rate is used to calculate extract capacity. The size of patient information is raises then BER is zero but the original signal deteroiates. Curvelet transform removes the limitation of wavelet transform and watermarking technique. Hence the curvelet transform is very efficient technique.

Keywords

ECG steganography Adaptive LSB algorithm Watermark position selection Curvelet transform Chaos encryption for embed Key encryption 

Notes

Acknowledgements

I am greatly pleased to proof: M. V. Patil who guided me through my project curvelet based ECG steganography for protection of data.

References

  1. 1.
    Ibaida, A., Khalil, I.: Wavelet-based ECG steganography for protecting patient confidential information in point-of-care systems. In: IEEE Trans. Biomed. Eng, pp. 3322–3330. (2013)Google Scholar
  2. 2.
    Miyara, K., Chen, F., Nakao, Z.: Digital watermarking based on curvelet transform. Ninth Int. Symp. Signal Process. (2007)Google Scholar
  3. 3.
    Taby, A., Naima Fiete, F.: High capacity image steganography based on curvelet transform. In: Proc. Fourth Int. Conf. Dev. Systems Eng., pp. 191–196 (2011)Google Scholar
  4. 4.
    Ji, F., Huang, D., Deng, C., Zhang, Y., Miao, W.: Robust curvelet-domain image water-marking based on feature matching. Int. J. Comp. Math. 88, 3931–3941 (2011)CrossRefGoogle Scholar
  5. 5.
    Chen, S.T., Guo, Y.J., Huang, H.N., Kung, W.M., Tseng, K.K., Tu, S.Y.: Hiding patients confidential data in the ECG signal via transform-domain quantization scheme. J. Med. Syst. (2014)Google Scholar
  6. 6.
    Moody, G.B., Mark, R.: MIT-BIH arrhythmia database directory. In: MIT-BIH Database Distribution, Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology. Available from http://www.physionet.org/physiobank/database/html/mitdbdir/mitdbdir.htm (1992)
  7. 7.
    Chen, S.-T., Guo, Y.-J., Huang, H.-N., Kung, W.-M., Tseng, K.-K., Tu, S.-Y.: Hiding patients confidential data in the ECG signal via transform-domain quantization scheme. J. Med. Syst. 38–54. doi: https://doi.org/10.1007/s10916-014-0054-9 (2014)
  8. 8.
    Xu, J., Pang, H., Zhao, J.: Digital image watermarking algorithm based on fast curvelet transform. Software Engineering & Applications, 939–943. doi: https://doi.org/10.4236/jsea.2010.310111 (2010)
  9. 9.
    Degadwala, S., Thakkar, A., Nayak, R.: High capacity ımage steganography using curvelet transform and bit plane slicing. Int. J. Adv. Res. Comp. Sci. ISSN No. 0976–5697, 4 (2013)Google Scholar
  10. 10.
    Jero, E., Ramu, P., Ramakrishnan, S.: ECG steganography using curvelet transforms. Biomed. Sig. Process. Control 22, 161–169. doi: https://doi.org/10.1049/el.2015.3218
  11. 11.
    Jero, S.E., Ramu, P., Ramakrishnan, S.: Discrete wavelet transform and singular value decomposition based ECG steganography for secured patient ınformation transmission. J. Med. Syst. 38–132. doi: https://doi.org/10.1007/s10916-014-0132-z (2014)
  12. 12.
    Kourav, A., Singh, P.: Review on curvelet transform and its applications. Asian. J. Electr. Sci. ISSN 2249–6297. 2(1) pp. 9–13, (2013)Google Scholar

Copyright information

© Springer International Publishing AG  2018

Authors and Affiliations

  1. 1.Deptartment of ElectronicsBharti Vidyapeeth University College of EngineeringPuneIndia

Personalised recommendations