[1] H. Kohad, V. R .Ingle, and M. A. Gaikwad ―An Overview of Speech Encryption techniques‖, International Journal of Engineering Research and Development ISSN, vol. 3, Issue 4 , pp. 29-32, 2012.
[2] L. Muda, M. Begam and I. Elamvazuthi ''Voice Recognition Algorithms using Mel Frequency Cepstral Coefficient (MFCC) and Dynamic Time Warping (DTW) Techniques'', Journal of Computing, Vol. 2, ISSN 2151-9617, March 2010.
[3] Farsana F J, Dr.K.Gopakumar, Private Key Encryption of Speech Signal Based on Three Dimensional Chaotic Map, International Conference on Communication and Signal Processing, pp. 2197-2201,
April 6-8, 2017.
[4] Y.Saleem,M.Amjad,M.H.Rahman,F.Hayat,T.Izhar,M.Saleem,”Speech Encryption,Implementation of One Time Pad Algorithm in Matlab” Pakistan Journal of Science,Vol.65, pp 114-118,March 2013.
[5] R.Aparna,Dr.PL.Chithra,Role of Windowing Techniques in Speech Signal Processing For Enhanced Signal Cryptography,Advanced Engineering Research amd Applications, Chapter 28,Volume V,pp.
446-458,2017.
[6] A. K. Jain, A. A. Ross, and K. Nandakumar, Introduction to Biometrics (Springer, 2017).
[7] V. M. Patel, N. K. Ratha, and R. Chellappa, “Cancelable biometrics: a review,” IEEE Signal Process. Mag. 32, 54–65 (2015).
[8] H. Kaur and P. Khanna, “Non-invertible biometric encryption to generate cancelable biometric templates,” in Proceedings of the World Congress on Engineering and Computer Science, San Francisco, California, 2017, Vol. I, pp. 1–4.
[9] Al Saad, S. N., & Eman, H. (2014) A speech encryption based on chaotic maps. International Journal of Computer Applications, 93(4).
[10] Campbell, J. P. (1997). Speaker recognition: a tutorial. Proceedings of the IEEE, 85(9), 1437–1462.
[11] Furui, S. (1996). An overview of speaker recognition technology. The Kluwer International Series in Engineering and Computer Science, 355, 31–55.
[12] Goldburg, B., Sridharan, S., & Dawson, E. (1990). Speech encryption in the transform domain. Electronics Letters, 26(10), 655–657.
[13] Goldburg, B., Sridharan, S., & Dawson, E. (1993) Design and cryptanalysis of transform-based analog speech scramblers. IEEE on Select Areas on Communications, 11(5), 735–744.
[14] Stallings, W. (2017) Cryptography and network, security: Principles and practice (7th edn.). Upper Saddle River: Prentice-Hall.
[15] Gupta, S., Jaafar, J., Ahmad, W. F. W., & Bansal A. (2013) Feature extraction using MFCC. Signal & Image Processing: An International Journal (SIPIJ), 4(4), 101.
[16] Kohad H., Ingle V. R., & Gaikwad M. A. (2012). An overview of speech encryption techniques, International Journal of Engineering Research and Development, 3(4), 29–32.
[17] Kurzekar, P. K., Deshmukh, R. R., Waghmare, V. B., & Shrishrimal, P. P. (2014). A comparative study of feature extraction techniques for speech recognition system. IJIRSET, 3, 18006–18016.
[18] Manjunath, G., & Anand, G. V. (2002). Speech encryption using circulant transformations. Proceedings IEEE, International Conference Multimedia and Expo, vol. 1, pp. 553–556, August, 2002.
[19] Milton, R. M. A time and frequency-domain speech scrambler, COMSIG 1989 Proceedings, Southern African Conference, pp. 125– 130, June 1989
[20] Muda, L., Begam, M., & Elamvazuthi, I. (2010). Voice recognition algorithms using mel frequency cepstral coefficient (MFCC) and dynamic time warping (DTW) techniques. Journal of Computing, 2.