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A multi-tier security system (SAIL) for protecting audio signals from malicious exploits

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Abstract

This paper proposes a multi-tier SegmEntation ECC Desegmentation (SEED) model to suit audio cryptosystem for Securing Audio sIgnal (SAIL) based on discrete wavelet transform and elliptic curve encryption. It is aimed with the prospect of enhancing the level of security in digital audio communication for unreliable public networks. The proposed SAIL system works as a multitier SEED model by performing segmentation, DWT compression, ECC encryption and desegmentation. In the reverse process, this multitier model proceeds with segmentation, decryption, decompression, and desegmentation. The novelty of this work relies on the adoption of ECC for encryption as it is first of its kind in audio streaming. The selection of appropriate ECC curve is a real challenge, and complex multiplication method has been applied. ECC has been chosen for encryption as it has been identified as a discrete logarithm problem which is resistant to be attacked by quantum computers. The performance of the recommended SAIL cryptosystem has been tested using different audio samples characterizing human voice, animal voice and Instrumental music. Analysis of the proposed model shows the effectiveness for fast audio encryption as it works on compressed data and also computationally simple. Various statistical analysis have been done on the proposed model, and the obtained result ratifies better level protection of audio signals from different security threats and can be recommended for multi channel audio processing.

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References

  • Akgül, A., & Kaçar, S. (2015). An audio data encryption with single and double dimension discrete-time chaotic systems. Turkish Online Journal of Science & Technology, 5(3), 14–23

    Google Scholar 

  • Al Saad, S. N., & Hato, E. (2014). A speech encryption based on chaotic maps. International Journal of Computer Applications, 93(4), 19–28.

    Google Scholar 

  • al-Karim, A., Al-Jalil, M. A., & Qays, I. (2013). Speech encryption using a chaotic map and blowfish algorithms. Journal of Basrah Researches (Sciences), 39(2), 68–76.

    Google Scholar 

  • Alwahbani, S. M. H., & Bashier, E. B. M. (2013). Speech scrambling based on chaotic maps and one-time pad. 2013 International Conference on Computing, Electrical and Electronics Engineering (ICCEEE), IEEE (pp. 128–133).

  • Anees, A. (2015). An image encryption scheme based on Lorenz system for low profile applications. 3D Research, 6(3), 1–10.

    Article  Google Scholar 

  • Asok, S. B., et al. (2013). A secure cryptographic scheme for audio signals. 2013 International Conference on Communications and Signal Processing (ICCSP), IEEE.

  • Augustine, N., George, S. N., & Pattathil, D. P. (2015). An audio encryption technique through compressive sensing and Arnold transform. International Journal of Trust Management in Computing and Communications, 3(1), 74–92.

    Article  Google Scholar 

  • Barni, M., Bartolini, F., & Piva, A. (2001). Improved wavelet-based watermarking through pixel-wise masking. IEEE Transactions on Image Processing, 10(5), 783–791.

    Article  MATH  Google Scholar 

  • Chen, L. H., & Lin, J. J. (2003). Mean quantization based image watermarking. Image and Vision Computing, 21(8), 717–727.

    Article  Google Scholar 

  • Cichowski, J., & Czyzewski, A. (2012). Sensitive audio data encryption for multimodal surveillance systems. In Audio Engineering Society Convention 132. Audio Engineering Society.

  • Ciptasari, R. W., Rhee, K. H., & Sakurai, K. (2014). An enhanced audio ownership protection scheme based on visual cryptography. EURASIP Journal on Information Security, 1, 2.

    Article  Google Scholar 

  • Datta, K., & Gupta, I. S. (2013). Partial encryption and watermarking scheme for audio files with controlled degradation of quality. Multimedia Tools and Applications, 64(3), 649–669.

    Article  Google Scholar 

  • Dengre, A., & Gawande, A. D. (2015). Audio encryption and digital image watermarking in an uncompress video. International Journal of Advances in Applied Sciences, 4(2), 66–72.

    Google Scholar 

  • Eldin, S. M. S., et al. (2015). New audio encryption package for TV cloud computing. International Journal of Speech Technology, 18(1), 131–142.

    Article  Google Scholar 

  • Elkholy, M. M., Hennawy, H. M. E. L., & Elkouny, A. (2015). Design and implementation of hyperchaotic masking system for secured audio transmission. 2015 Tenth International Conference on Computer Engineering & Systems (ICCES), IEEE.

  • Elshamy, A. M., et al. (2013). Optical image encryption based on chaotic baker map and double random phase encoding. Journal of Lightwave Technology, 31(15), 2533–2539.

    Article  Google Scholar 

  • Fazeen, M., Bajwa, G., & Dantu, R. (2014). Context-aware multimedia encryption in mobile platforms. Proceedings of the 9th Annual Cyber and Information Security Research Conference. ACM

  • Hedelin, P., Nordén, F., & Skoglund, J. (1999). SD optimization of spectral coders. 1999 IEEE Workshop on Speech Coding Proceedings, IEEE.

  • Iyer, S. C., Sedamkar, R. R., & Gupta, S. (2016). A novel idea on multimedia encryption using hybrid crypto approach. Procedia Computer Science, 79, 293–298.

    Article  Google Scholar 

  • James, S. P., George, S. N., & Deepthi, P. P. (2014). An audio encryption technique based on LFSR based alternating step generator. 2014 IEEE International Conference on Electronics, Computing and Communication Technologies (IEEE CONECCT), IEEE

  • Kim, S. W., Kim, Y. G., & Simon, M. K. (2004). Generalized selection combining based on the log-likelihood ratio. IEEE Transactions on Communications, 52(4), 521–524.

    Article  Google Scholar 

  • Kohad, H., Ingle, V. R., & Gaikwad, M. A. (2012). An overview of speech encryption techniques. International Journal of Engineering Research and Development, 3, 29–32.

    Google Scholar 

  • Kulkarni, S. A., & Patil, S. B. (2015). A robust encryption method for speech data hiding in digital images for optimized security. 2015 International Conference on Pervasive Computing (ICPC), IEEE.

  • Kwon, J. K., Park, S., & Sung, D. K. (2006). Collision mitigation by log-likelihood ratio (LLR) conversion in orthogonal code-hopping multiplexing. IEEE Transactions on Vehicular Technology, 55(2), 709–717.

    Article  Google Scholar 

  • Langelaar, G. C., Setyawan, I., & Lagendijk, R. L. (2000). Watermarking digital image and video data. A state-of-the-art overview. IEEE Signal processing magazine, 17(5), 20–46.

    Article  Google Scholar 

  • Li, H., et al. (2009). A novel audio scrambling algorithm in variable dimension space. 11th International Conference on Advanced Communication Technology, 2009, ICACT. (Vol. 3, pp 1647–1651). IEEE.

  • Lima, J. B., & da Silva Neto, E. F. (2016). Audio encryption based on the cosine number transform. Multimedia Tools and Applications, 75(14), 8403–8418.

    Article  Google Scholar 

  • Lin, C. Y., & Chang, S. F. (2001). A robust image authentication method distinguishing JPEG compression from malicious manipulation. IEEE Transactions on Circuits and Systems for Video Technology, 11(2), 153–168.

    Article  Google Scholar 

  • Liu, H., & Wang, X. (2010). Color image encryption based on one-time keys and robust chaotic maps. Computers & Mathematics with Applications, 59(10), 3320–3327.

    Article  MathSciNet  MATH  Google Scholar 

  • Lu, X., et al. (2012). Digital audio information hiding based on Arnold transformation and double random-phase encoding technique. Optik-International Journal for Light and Electron Optics, 123(8), 697–702.

    Article  Google Scholar 

  • Mermoul, A., & Belouchrani, A. (2010). A subspace-based method for speech encryption. 2010 10th International Conference on, Information Sciences Signal Processing and their Applications (ISSPA). IEEE.

  • Mostafa, A., et al. (2015). Speech encryption using two-dimensional chaotic maps. 2015 11th International Computer Engineering Conference (ICENCO), IEEE

  • Nguyen, H. H., Mehaoua, A., & Hong, J. W. K. (2013). Secure medical tele-consultation based on voice authentication and realtime audio/video encryption. 2013 First International Symposium on Future Information and Communication Technologies for Ubiquitous HealthCare (Ubi-HealthTech), IEEE.

  • Petitcolas, Fabien, A. P., Ross, J.. Anderson, & Markus, G., & Kuhn (1999). Information hiding-a survey. Proceedings of the IEEE 87(7): 1062–1078.

    Article  Google Scholar 

  • Rashidi, B., & Rashidi, B. (2013). FPGA based A new low power and self-timed AES 128-bit encryption algorithm for encryption audio signal. International Journal of Computer Network and Information Security, 5(2), 10.

    Article  Google Scholar 

  • Refregier, P., & Javidi, B. (1995). Optical image encryption based on input plane and Fourier plane random encoding. Optics Letters, 20(7), 767–769.

    Article  Google Scholar 

  • Sadkhan, S. B., & Mohammed, R. S. (2015). Proposed random unified chaotic map as PRBG for voice encryption in wireless communication. Procedia Computer Science, 65, 314–323.

    Article  Google Scholar 

  • Sharma, D. (2012). Five level cryptography in speech processing using multi hash and repositioning of speech elements. International Journal of Emerging Technology and Advanced Engineering, 2(3), 21–26

    Google Scholar 

  • Sheu, L. J. (2011). A speech encryption using fractional chaotic systems. Nonlinear Dynamics, 65(1), 103–108.

    Article  MathSciNet  MATH  Google Scholar 

  • Tamimi, A. A., & Abdalla, A. M. (2014). An audio shuffle-encryption algorithm. Proceedings of the World Congress on Engineering and Computer Science. San Francisco, USA: WCECS

  • Tong, X. J., et al. (2015). A fast encryption algorithm of the color image based on the four-dimensional chaotic system. Journal of Visual Communication and Image Representation, 33, 219–234.

    Article  Google Scholar 

  • Wang, S., & Fan, Y. (2010). A watermarking algorithm of gray image based on histogram statistical characteristics. Computer Technology and Development, 1, 045.

    Google Scholar 

  • Washio, S., & Watanabe, Y. (2014). Security of audio secret sharing scheme encrypting audio secrets with bounded shares. 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE.

  • Wu, Y., & Ng, B. P. (2002). Speech scrambling with Hadamard transform in the frequency domain. Signal Processing, 2002 6th International Conference on. Vol. 2. IEEE

  • Yang, W., Benbouchta, M., & Robert, Y. (1998). Performance of the modified bark spectral distortion as an objective speech quality measure. Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on. Vol. 1. IEEE.

  • Zeng, L., et al. (2012). Scrambling-based speech encryption via compressed sensing. EURASIP Journal on Advances in Signal Processing, 2012(1), 257.

    Article  Google Scholar 

  • Zhang, C., Wang, J., & Wang, X. (2008). Digital image watermarking algorithm with double encryption by Arnold transform and logistic. NCM’08 Fourth International Conference on Networked Computing and Advanced Information Management, Vol. 1. IEEE

  • Zhao, H., et al. (2014). Dual key speech encryption algorithm based underdetermined BSS. The Scientific World Journal. https://doi.org/10.1155/2014/974735

    Google Scholar 

Download references

Acknowledgements

This part of this research work is supported by Department of Science and Technology (DST), Science and Engineering Board (SERB), Government of India under the ECR Grant (ECR/2017/000679/ES).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, School of Computing, SASTRA Deemed University, Thanjavur, TN, India

    N. Sasikaladevi, K. Geetha & K. N. Venkata Srinivas

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  1. N. Sasikaladevi
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  2. K. Geetha
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  3. K. N. Venkata Srinivas
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Correspondence to N. Sasikaladevi.

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Sasikaladevi, N., Geetha, K. & Venkata Srinivas, K.N. A multi-tier security system (SAIL) for protecting audio signals from malicious exploits. Int J Speech Technol 21, 319–332 (2018). https://doi.org/10.1007/s10772-018-9510-0

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  • DOI: https://doi.org/10.1007/s10772-018-9510-0

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