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A metaheuristic method to hide MP3 sound in JPEG image

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Abstract

VoIP is much in use these days as many applications over phone, tablet, and computers are available. The data in VoIP can be collected for further analysis or it can be intercepted. VoIP privacy and security is a major concern these days. This paper discusses an implementation of hiding a sound file in a digital image. This sound can be voice, VoIP data or a song. In this approach, an MP3 file was used with JPEG image for implementation. The rightmost k-LSB of pixels was utilized to embed MP3 bits into a pixel. The pixels are so chosen that the distortion in the image would be minimized due to embedding. This is implemented in such a way that makes it difficult to conclude about the existence of the hidden data inside the image. A metaheuristic technique Cuckoo Search was used to find most suitable solutions for minimization. The results are also compared with existing techniques of steganography.

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References

  1. Rhee MY (1994) Cryptography and secure communication. McGraw-Hill Book Co, Singapore

    MATH  Google Scholar 

  2. Jinn-K J, Yuh-Min T (1996) On the security of image encryption method. Infor Process Lett 60(5):261–265

    Article  MathSciNet  MATH  Google Scholar 

  3. Bourbakis N, Alexopoulos C (1992) Picture data encryption using scan patterns. Pattern Recognit 25(6):567–581

    Article  Google Scholar 

  4. Bender W, Gruhl D, Morimoto N, Lu A (1996) Techniques for data hiding. IBM Syst J 35(3, 4):313–336

  5. Gupta A, Chaudhary A (2014) Hiding sound in image by k-LSB mutation using Cuckoo Search. In: Second IEEE-INNS international symposium on computational and business intelligence, New Delhi, India, 7–8 Dec 2014

  6. Fong S, Deb S, Chaudhary A (2015) A review of metaheuristics on robotics. In: Computers and electrical engineering, vol 43, Elsevier, pp 278–291

  7. Adelson E (1990) Digital signal encoding and decoding apparatus. US Patent 4,939,515 1990

  8. Turner LF (1989) Digital data security system. Patent IPN wo 89 08915

  9. Van Schyndel RG, Tirkel A, Osborne CF (1994) A digital watermark. In: Image processing, 1994. Proceedings ICIP-94, IEEE international conference, vol 2, IEEE

  10. Chaudhary A et al (2012) A hash based approach for secure keyless steganography in lossless RGB images. In: Proceedings of the 22nd graphicon: international conference on computer graphics and vision, Moscow, Russia, 1–5 Oct 2012, pp 80–83

  11. Wang R-Z, Lin C-F, Lin J-C (2001) Image hiding by optimal LSB substitution and genetic algorithm. Pattern Recognit 34(3):671–683

    Article  MATH  Google Scholar 

  12. Li X, Wang J (2007) A steganographic method based upon JPEG and particle swarm optimization algorithm. Inf Sci 177(15):3099–3109

    Article  Google Scholar 

  13. Bedi P, Bansal R, Sehgal P (2011) Using PSO in image hiding scheme based on LSB substitution. In: Proceedings of first international conference on advances in computing and communications, vol 192. Springer, Berlin, pp 259–268

  14. Singh KSMJ, Elamvazuthi I, Shaari KZK, Lima FV (2015) PID tuning control strategy using Cuckoo Search algorithm. In: 2015 IEEE student conference on research and development, Kuala Lumpur, pp 129–133

  15. Bhoye M, Purohit SN, Trivedi IN, Pandya MH, Jangir P, Jangir N (2016) Energy management of renewable energy sources in a microgrid using Cuckoo Search Algorithm. In: 2016 IEEE students’ conference on electrical, electronics and computer science, India, 2016, pp 1–6

  16. Cakmak R, Altas IH (2016) Scheduling of domestic shiftable loads via Cuckoo Search optimization algorithm. In: 2016 4th international istanbul smart grid congress and fair, Istanbul, 2016, pp 1–4

  17. Soto R, Crawford B, Barraza J, Johnson F, Paredes F (2015) Solving pre-processed set covering problems via Cuckoo Search and Lévy flights. In: 2015 10th Iberian conference on information systems and technologies, Aveiro, 2015, pp 1–6

  18. Cheung NJ, Ding XM, Shen HB (2016) A nonhomogeneous Cuckoo Search algorithm based on quantum mechanism for real parameter optimization. In: IEEE transactions on cybernetics, pp 1–12. doi:10.1109/TCYB.2016.2517140

  19. Gerami P, Subariah I, Morteza B (2012) Least significant bit image steganography using particle swarm optimization and optical pixel adjustment. Int J Comput Appl 55(2):20–25

    Google Scholar 

  20. Mohamed M, Al-Afari F, Bamatraf MA (2011) Data hiding by LSB substitution using genetic optimal key-permutation. Int Arab J e-Technol 2(1):11–17

    Google Scholar 

  21. http://www.multiweb.cz/twoinches/mp3inside.htm

  22. http://professionaltag.sourceforge.net/WhatIsID3.html

  23. Yang X-S, Suash D (2009) Cuckoo Search via Lévy flights. In: Nature biologically inspired computing. NaBIC 2009. World Congress on IEEE 2009

  24. Barthelemy P et al (2008) A Lévy flight for light. Nature 453(7194):495–498

    Article  Google Scholar 

  25. Gutowski M (2001) Lévy flights as an underlying mechanism for global optimization algorithms. arXiv preprint math-ph/0106003

  26. Pavlyukevich I (2007) Lévy flights, non-local search and simulated annealing. J Comput Phys 2007(226):1830–1844

    Article  MathSciNet  MATH  Google Scholar 

  27. Civicioglu P, Besdok E (2013) A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms. Artif Intell Rev 39(4):315–346

    Article  Google Scholar 

  28. Rajabioun R (2011) Cuckoo optimization algorithm. Appl Soft Comput 11(8):5508–5518

    Article  Google Scholar 

  29. Valian E, Mohanna S, Tavakoli S (2011) Improved Cuckoo Search algorithm for feedforward neural network training. Int J Artif Intell Appl 2(3):36–43

    Google Scholar 

  30. Walton S et al (2011) Modified Cuckoo Search: a new gradient free optimisation algorithm. Chaos Solitons Fractals 44(9):710–718

    Article  Google Scholar 

  31. Huynh-Thu Q, Ghanbari M (2008) Scope of validity of PSNR in image/video quality assessment. Electron Lett 44(13):800–801

    Article  Google Scholar 

  32. Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612

    Article  Google Scholar 

  33. http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/VELDHUIZEN/node18.html

  34. http://en.wikipedia.org/wiki/Peak_signal-to-noise_ratio

  35. Lin IC, Lin YB, Wang CM (2009) Hiding data in spatial domain images with distortion tolerance. Comput Stand Interfaces 31(2):458–464

    Article  MathSciNet  Google Scholar 

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Correspondence to Ankit Chaudhary.

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Gupta, A., Chaudhary, A. A metaheuristic method to hide MP3 sound in JPEG image. Neural Comput & Applic 30, 1611–1618 (2018). https://doi.org/10.1007/s00521-016-2759-9

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