Security of Electronic Patient Record using Imperceptible DCT-SVD based Audio Watermarking Technique
Abstract
technique is presented to secure the electronic patient
record of Parkinson’s Disease (PD) affected patient. The proposed
DCT-SVD based watermarking technique introduces minimal
changes in speech such that the accuracy in classification of PD
affected person’s speech and healthy person’s speech is retained.
To achieve high imperceptibility the voiced part of the speech is
considered for embedding the watermark. It is shown that the
proposed watermarking technique is robust to common signal
processing attacks. The practicability of the proposed technique is
tested: by creating an android application to record & watermark
the speech signal. The classification of PD affected speech is done
using Support Vector Machine (SVM) classifier in cloud server.
Full Text:
PDFReferences
M. M. Baig, H. Gholamhosseini, Smart health monitoring systems: An
overview of design and modeling, Journal of Medical Systems 37 (2)
(2013) 9898.
A.-H. Ali, An imperceptible and robust audio watermarking algorithm,
EURASIP Journal on Audio, Speech, and Music Processing 2014 (1)
(2014) 37.
M. Shahbakhi, D. T. Far, E. Tahami, Speech analysis for diagnosis of
parkinson‘s disease using genetic algorithm and support vector machine,
Journal of Biomedical Science and Engineering 7 (4) (2014) 147–156.
A. Tsanas, M. A. Little, P. E. McSharry, J. Spielman, L. O. Ramig, Novel
speech signal processing algorithms for high-accuracy classification of
parkinson’s disease, IEEE Transactions on Biomedical Engineering 59 (5)
(2012) 1264–1271.
Y. Zhang, Can a smartphone diagnose parkinson disease? a deep neural
network method and telediagnosis system implementation, Parkinson‘s
Disease 2017.
S. A. Parah, J. A. Sheikh, F. Ahad, N. A. Loan, G. M. Bhat, Information
hiding in medical images: a robust medical image watermarking system
for e-healthcare, Multimedia Tools and Applications 76 (8) (2017) 10599–
N. A. Loan, S. A. Parah, J. A. Sheikh, J. A. Akhoon, G. M. Bhat, Hiding
electronic patient record (epr) in medical images: A high capacity and
computationally efficient technique for e-healthcare applications, Journal
of Biomedical Informatics 73 (2017) 125–136.
S. A. Parah, J. A. Sheikh, F. Ahad, G. Bhat, High capacity and secure
electronic patient record (epr) embedding in color images for iot driven
healthcare systems, in: Internet of Things and Big Data Analytics Toward
Next-Generation Intelligence, Springer, 2018, pp. 409–437.
N. Dey, A. S. Ashour, S. Chakraborty, S. Banerjee, E. Gospodinova,
M. Gospodinov, A. E. Hassanien, Watermarking in biomedical signal
processing, in: Intelligent Techniques in Signal Processing for Multimedia
Security, Springer, 2017, pp. 345–369.
M. Alhussein, G. Muhammad, Watermarking of parkinson disease
speech in cloud-based healthcare framework, International Journal of
Distributed Sensor Networks 11 (10) (2015) 264575.
Z. Ali, M. Imran, W. Abdul, M. Shoaib, An Innovative Algorithm
for Privacy Protection in a Voice Disorder Detection System, Springer
International Publishing, Cham, 2018, pp. 228–233.
W. Bender, D. Gruhl, N. Morimoto, A. Lu, Techniques for data hiding,
IBM Systems Journal 35 (3.4) (1996) 313–336.
N. Cvejic, T. Seppanen, Increasing the capacity of lsb-based audio
steganography, in: Multimedia Signal Processing, 2002 IEEE Workshop
on, 2002, pp. 336–338.
K. Bhowal, D. Bhattacharyya, A. Jyoti Pal, T.-H. Kim, A ga based audio
steganography with enhanced security, Telecommun. Syst. 52 (4) (2013)
–220.
A. Kanhe, G. Aghila, C. S. Kiran, C. Ramesh, G. Jadav, M. Raj, Robust
audio steganography based on advanced encryption standards in temporal
domain, in: Advances in Computing, Communications and Informatics
(ICACCI), 2015 International Conference on, 2015, pp. 1449–1453.
Y. Erfani, S. Siahpoush, Robust audio watermarking using improved ts
echo hiding, Digital Signal Processing 19 (5) (2009) 809–814.
V. Korzhik, G. Morales-Luna, I. Fedyianin, Audio watermarking based
on echo hiding with zero error probability, International Journal of Computer
Science and Applications, Technomathematics Research Foundation
(1) (2013) 1–10.
M. Fallahpour, D. Megias, Audio watermarking based on fibonacci numbers,
IEEE/ACM Transactions on Audio, Speech, and Language Processing
(8) (2015) 1273–1282.
M. Fallahpour, D. Megias, Robust audio watermarking based on fibonacci
numbers, in: 2014 10th International Conference on Mobile Adhoc
and Sensor Networks, 2014, pp. 343–349.
S. Ahani, S. Ghaemmaghami, Z. J. Wang, A sparse representationbased
wavelet domain speech steganography method, Audio, Speech, and
Language Processing, IEEE/ACM Transactions on 23 (1) (2015) 80–91.
P. Shah, P. Choudhari, S. Sivaraman, Adaptive wavelet packet based
audio steganography using data history, in: 2008 IEEE Region 10 and
the Third international Conference on Industrial and Information Systems,
, pp. 1–5.
B. E. Sakar, M. E. Isenkul, C. O. Sakar, A. Sertbas, F. Gurgen,
S. Delil, H. Apaydin, O. Kursun, Collection and analysis of a parkinson
speech dataset with multiple types of sound recordings, IEEE Journal of
Biomedical and Health Informatics 17 (4) (2013) 828–834.
B. Woldert-Jokisz, Saarbruecken voice database, Institute of Phonetics,
Saarland University.
Rekik, S., Guerchi, D., Selouani, S.A., Hamam, H.: Speech steganography
using wavelet and fourier transforms. EURASIP Journal on Audio,
Speech, and Music Processing 2012(1), 1–14 (2012). https://doi.org/10.
/1687-4722-2012-20
M. A. Little, P. E. McSharry, E. J. Hunter, J. Spielman, L. O. Ramig,
et al., Suitability of dysphonia measurements for telemonitoring of parkinson’s
disease, IEEE transactions on biomedical engineering 56 (4) (2009)
–1022.
Refbacks
- There are currently no refbacks.
International Journal of Electronics and Telecommunications
is a periodical of Electronics and Telecommunications Committee
of Polish Academy of Sciences
eISSN: 2300-1933