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Beta Chaotic Map Based Image Steganography

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International Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019) (CISIS 2019, ICEUTE 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 951))

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Abstract

Steganography is one of the growing security fields. It is the science of embedding sensitive data in images using different techniques. In this paper, we proposed a steganographic scheme based on Beta chaotic map in order to embed secret images bits into cover images. Thus a secure transmission of data could be established. We applied the PSNR, MSE and histogram tests on the obtained images and comparisons were made with different existing methods; prove that our proposed scheme has a good steganographic quality.

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References

  1. Borda, M.: Fundamentals in Information Theory and Coding. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-20347-3

    Book  MATH  Google Scholar 

  2. Katzenbeisser, S., Petitcolas, F.: Information Hiding Techniques for Steganography and Digital Watermarking. Artech house, Norwood (2000)

    Google Scholar 

  3. Tang, W., Li, B., Tan, S., Barni, M., Huang, J.: CNN-based adversarial embedding for image steganography. IEEE Trans. Inf. Forensics Secur. PP, 1 (2019)

    Article  Google Scholar 

  4. Pal, A.K., Naik, K., Agarwal, R.: A steganography scheme on JPEG compressed cover image with high embedding capacity. Int. Arab J. Inf. Technol. 16(1), 116–124 (2019)

    Google Scholar 

  5. Duan, X., Jia, K., Li, B., Guo, D., Zhang, E., Qin, C.: Reversible image steganography scheme based on a U-Net structure. IEEE Access 7, 9314–9323 (2019)

    Article  Google Scholar 

  6. Sharif, A., Mollaeefar, M., Nazari, M.: Multimed. Tools Appl. 76, 7849 (2017). https://doi.org/10.1007/s11042-016-3398-y

    Article  Google Scholar 

  7. Prasad, S., Pal, A.K.: Logistic map-based image steganography scheme using combined LSB and PVD for security enhancement. In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds.) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol. 814. Springer, Singapore (2019)

    Google Scholar 

  8. Prasad, S., Pal, A.K.: An RGB colour image steganography scheme using overlapping block-based pixel-value differencing. R. Soc. Open Sci. 4(4), 161066 (2017)

    Article  MathSciNet  Google Scholar 

  9. Dash, S., Das, M.N., Das, M.: Secured image transmission through region-based steganography using chaotic encryption. In: Behera, H., Nayak, J., Naik, B., Abraham, A. (eds.) Computational Intelligence in Data Mining. Advances in Intelligent Systems and Computing, vol. 711. Springer, Singapore (2019)

    Google Scholar 

  10. Zahmoul, R., Ejbali, R., Zaied, M.: Image encryption based on new Beta chaotic maps. Opt. Lasers Eng. 96, 39–49 (2017)

    Article  Google Scholar 

  11. Zahmoul, R., Zaied, M.: Toward new family beta maps for chaotic image encryption. In: 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 004052–004057. IEEE, October 2016

    Google Scholar 

  12. Gashim, L.L., Hussein, K.Q.: A new algorithm of encryption and decryption of image using combine chaotic mapping. Iraqi J. Inf. Technol. 9, 1–16 (2018)

    Google Scholar 

  13. Jain, M.: Medical image steganography using dynamic decision tree, piecewise linear chaotic map, and hybrid cryptosystem. Int. J. Appl. Eng. Res. 13(15), 12353–12363 (2018)

    Google Scholar 

  14. Amar, C.B., Zaied, M., Alimi, A.: Beta wavelets. synthesis and application to lossy image compression. Adv. Eng. Softw. 36(7), 459–474 (2005)

    Article  Google Scholar 

  15. ElAdel, A., Ejbali, R., Zaied, M., Amar, C.B.: A hybrid approach for content-based image retrieval based on fast beta wavelet network and fuzzy decision support system. Mach. Vis. Appl. 27(6), 781–799 (2016)

    Article  Google Scholar 

  16. Ejbali, R., Zaied, M., Amar, C.B.: Face recognition based on Beta 2D elastic bunch graph matching. In: HIS, pp. 88–92, December 2013

    Google Scholar 

  17. Chanu, Y.J., Singh, K.M., Tuithung, T.: Image steganography and steganalysis: a survey. Int. J. Comput. Appl. 52(2), 1–11 (2012)

    Google Scholar 

  18. Khodaei, M., Faez, K.: Image hiding by using genetic algorithm and LSB substitution. In: International Conference on Image and Signal Processing, pp. 404–411. Springer, Heidelberg, June 2010

    Google Scholar 

  19. Bedi, P., Bansal, R., Sehgal, P.: Using PSO in image hiding scheme based on LSB substitution. In: International Conference on Advances in Computing and Communications, pp. 259–268. Springer, Heidelberg, July 2011

    Google Scholar 

  20. Rajendran, S., Doraipandian, M.: Chaotic map based random image steganography using LSB technique. IJ Netw. Secur. 19(4), 593–598 (2017)

    Google Scholar 

  21. El Adel, A., Zaied, M., Amar, C.B.: Learning wavelet networks based on multiresolution analysis: application to images copy detection. In 2011 International Conference on Communications, Computing and Control Applications (CCCA), pp. 1–6. IEEE, March 2011

    Google Scholar 

  22. Ejbali, R., Zaied, M., Amar, C.B.: Multi-input multi-output beta wavelet network: modeling of acoustic units for speech recognition. arXiv preprint arXiv:1211.2007 (2012)

  23. Zaied, M., Mohamed, R., Amar, C.B.: A power tool for Content-based image retrieval using multiresolution wavelet network modeling and dynamic histograms. Int. Rev. Comput. Softw. (IRECOS) 7(4), 1435–1444 (2012)

    Google Scholar 

  24. Jemai, O., Ejbali, R., Zaied, M., Amar, C.B.: A speech recognition system based on hybrid wavelet network including a fuzzy decision support system. In: Seventh International Conference on Machine Vision (ICMV 2014), vol. 9445, p. 944503. International Society for Optics and Photonics, February 2015

    Google Scholar 

  25. Teyeb, I., Jemai, O., Zaied, M., Amar, C.B.: A drowsy driver detection system based on a new method of head posture estimation. In: International Conference on Intelligent Data Engineering and Automated Learning, pp. 362–369. Springer, Cham, September 2014

    Google Scholar 

  26. Ejbali, R., Zaied, M., Amar, C.B.: Intelligent approach to train wavelet networks for recognition system of arabic words. In: KDIR, pp. 518–522, October 2010

    Google Scholar 

  27. Hassairi, S., Ejbali, R., Zaied, M.: Supervised image classification using deep convolutional wavelets network. In: 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI), pp. 265-271. IEEE, November 2015

    Google Scholar 

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Acknowledgment

The authors would like to acknowledge the financial support of this work by grants from General Direction of Scientific Research (DGRST), Tunisia, under the ARUB program.

Author information

Authors and Affiliations

  1. Research Team in Intelligent Machines, National Engineering School of Gabes, 6072, Gabes, Tunisia

    Zahmoul Rim, Abbes Afef, Ejbali Ridha & Zaied Mourad

Authors
  1. Zahmoul Rim
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  2. Abbes Afef
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  3. Ejbali Ridha
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  4. Zaied Mourad
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Corresponding author

Correspondence to Zahmoul Rim .

Editor information

Editors and Affiliations

  1. Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  2. Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain

    Alicia Troncoso Lora

  3. University of Salamanca, Salamanca, Spain

    José António Sáez Muñoz

  4. Department of Industrial Engineering, University of A Coruña, A Coruña, Spain

    Héctor Quintián

  5. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Rim, Z., Afef, A., Ridha, E., Mourad, Z. (2020). Beta Chaotic Map Based Image Steganography. In: Martínez Álvarez, F., Troncoso Lora, A., Sáez Muñoz, J., Quintián, H., Corchado, E. (eds) International Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019). CISIS ICEUTE 2019 2019. Advances in Intelligent Systems and Computing, vol 951. Springer, Cham. https://doi.org/10.1007/978-3-030-20005-3_10

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