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Security of Electronic Patient Record using Imperceptible DCT-SVD based Audio Watermarking Technique

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A robust and highly imperceptible audio watermarking 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.
Słowa kluczowe
Twórcy
  • Department of Electronics and communication Engineering, National Institute of Technology Puducherry, Karaikal, India
  • Department of Computer Science and Engineering, National Institute of Technology Puducherry, Karaikal, India
Bibliografia
  • [1] M. M. Baig, H. Gholamhosseini, Smart health monitoring systems: An overview of design and modeling, Journal of Medical Systems 37 (2) (2013) 9898.
  • [2] A.-H. Ali, An imperceptible and robust audio watermarking algorithm, EURASIP Journal on Audio, Speech, and Music Processing 2014 (1) (2014) 37.
  • [3] 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.
  • [4] 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.
  • [5] Y. Zhang, Can a smartphone diagnose parkinson disease? a deep neural network method and telediagnosis system implementation, Parkinson‘s Disease 2017.
  • [6] 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) 10599–10633.
  • [7] 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.
  • [8] 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 healthcaresystems,in:InternetofThingsandBigDataAnalyticsToward Next-Generation Intelligence, Springer, 2018, pp. 409–437.
  • [9] 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.
  • [10] M. Alhussein, G. Muhammad, Watermarking of parkinson disease speech in cloud-based healthcare framework, International Journal of Distributed Sensor Networks 11 (10) (2015) 264575.
  • [11] 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.
  • [12] W. Bender, D. Gruhl, N. Morimoto, A. Lu, Techniques for data hiding, IBM Systems Journal 35 (3.4) (1996) 313–336.
  • [13] N. Cvejic, T. Seppanen, Increasing the capacity of lsb-based audio steganography, in: Multimedia Signal Processing, 2002 IEEE Workshop on, 2002, pp. 336–338.
  • [14] K. Bhowal, D. Bhattacharyya, A. Jyoti Pal, T.-H. Kim, A ga based audio steganography with enhanced security, Telecommun. Syst. 52 (4) (2013) 2197–220.
  • [15] 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.
  • [16] Y. Erfani, S. Siahpoush, Robust audio watermarking using improved ts echo hiding, Digital Signal Processing 19 (5) (2009) 809–814.
  • [17] 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 10 (1) (2013) 1–10.
  • [18] M. Fallahpour, D. Megias, Audio watermarking based on fibonacci numbers, IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (8) (2015) 1273–1282.
  • [19] M. Fallahpour, D. Megias, Robust audio watermarking based on fibonacci numbers, in: 2014 10th International Conference on Mobile Ad-hoc and Sensor Networks, 2014, pp. 343–349.
  • [20] 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.
  • [21] P. Shah, P. Choudhari, S. Sivaraman, Adaptive wavelet packet based audiosteganographyusingdatahistory,in:2008IEEERegion10andthe Third international Conference on Industrial and Information Systems, 2008, pp. 1–5.
  • [22] 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.
  • [23] B. Woldert-Jokisz, Saarbruecken voice database, Institute of Phonetics, Saarland University.
  • [24] 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/10.1186/1687-4722-2012-20
  • [25] 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) 1015–1022.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-baa8d0dd-d655-46c7-8085-7d0f53cb7a50
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