An Image Steganography using Particle Swarm Optimization and Transform Domain

  • Authors

    • Sanjutha MK
    2018-04-25
    https://doi.org/10.14419/ijet.v7i2.24.12139
  • Image steganography, DWT, Particle Swarm Optimization, IDWT, Security, Fitness function

  • As information technology is growing tremendously, one of the major concern is information security. A technique called image steganography is used to provide better security and for safeguarding the information. In image steganography, a secret image is put into recipient image so that only the receiver and sender will be aware of the secret message. Here in this paper, a secure, optimized scheme called particle swarm optimization is used to select the pixel efficiently for embedding the secret image in to cover image. PSO(Particle Swarm Optimization) decides pixel using fitness function which is based on the cost function. Cost function calculates entropy, edge and pixels intensity to evaluate fitness. Also, a technique called discrete wavelet transform has been employed to achieve robustness and statistical undetectability. The main aim of the proposed paper is to make better security and to obtain efficient PSNR and MSE values

     

     

  • References

    1. [1] S. K. Sabnis and R. N. Awale, “Statistical Steganalysis of High Capacity Image Steganography with Cryptography,†Procedia Comput. Sci., vol. 79, pp. 321–327, 2016.

      [2] P. Sethi and V. Kapoor, “A Proposed Novel Architecture for Information Hiding in Image Steganography by Using Genetic Algorithm and Cryptography,†Procedia Comput. Sci., vol. 87, pp. 61–66, 2016.

      [3] G. Swain, “Digital Image Steganography Using Variable Length Group of Bits Substitution,†Procedia Comput. Sci., vol. 85, no. Cms, pp. 31–38, 2016.

      [4] M. S. Subhedar and V. H. Mankar, “Image steganography using redundant discrete wavelet transform and QR factorization,†Comput. Electr. Eng., vol. 54, pp. 406–422, 2016.

      [5] M. Taherkhani and R. Safabakhsh, “A novel particle swarm optimization algorithm with adaptive inertia weight,†Appl. Soft Comput., vol. 38, pp. 281–295, 2016.

      [6] K. Ahmadi, A. Y. Javaid, and E. Salari, “An efficient compression scheme based on adaptive thresholding in wavelet domain using particle swarm optimization,†Signal Process. Image Commun., vol. 32, pp. 33–39, 2015.

      [7] R. Bhardwaj and V. Sharma, “Image Steganography Based on Complemented Message and Inverted Bit LSB Substitution,†Procedia Comput. Sci., vol. 93, no. September, pp. 832–838, 2016.

      [8] M. Jain, S. K. Lenka, and S. K. Vasistha, “Adaptive circular queue image steganography with RSA cryptosystem,†Perspect. Sci., vol. 8, pp. 417–420, 2016.

      [9] M. Tang, S. Zeng, X. Chen, J. Hu, and Y. Du, “An adaptive image steganography using AMBTC compression and interpolation technique,†Optik (Stuttg)., vol. 127, no. 1, pp. 471–477, 2016.

      [10] U. Dewangan, M. Sharma, and S. Bera, “Development and Analysis of Stego Image Using Discrete Wavelet Transform,†vol. 2, no. 1, 2013.

      [11] S. Hemalatha, U. D. Acharya, and A. Renuka, “Wavelet transform based steganography technique to hide audio signals in image,†Procedia Comput. Sci., vol. 47, no. C, pp. 272–281, 2014.

      [12] F. Mohsen, M. Hadhoud, K. Mostafa, and K. Amin, “A New Image Segmentation Method Based on Particle Swarm Optimization,†Int. Arab J. Inf. Technol., vol. 9, no. 5, pp. 487–493, 2012.

      [13] S. Gayathri and D. Venkatesan, “Particle Swarm Optimization and Discrete Wavelet Transform based Robust Image Watermarking,†Indian J. Sci. Technol., vol. 9, no. 48, 2016.

      [14] H. C. Tsai, “Unified particle swarm delivers high efficiency to particle swarm optimization,†Appl. Soft Comput. J., vol. 55, pp. 371–383, 2017.

      [15] M. S. Kiran, “Particle swarm optimization with a new update mechanism,†Appl. Soft Comput. J., vol. 60, pp. 670–678, 2017.

      [16] B. M. Chang, H. H. Tsai, and C. Y. Yen, “SVM-PSO based rotation-invariant image texture classification in SVD and DWT domains,†Eng. Appl. Artif. Intell., vol. 52, pp. 96–107, 2016.

      [17] P. Bedi, R. Bansal, and P. Sehgal, “Using PSO in a spatial domain based image hiding scheme with distortion tolerance,†Comput. Electr. Eng., vol. 39, no. 2, pp. 640–654, 2013.

      [18] W. Hong and T. S. Chen, “Reversible data embedding for high quality images using interpolation and reference pixel distribution mechanism,†J. Vis. Commun. Image Represent., vol. 22, no. 2, pp. 131–140, 2011.

      [19] N. N. El-Emam, “New data-hiding algorithm based on adaptive neural networks with modified particle swarm optimization,†Comput. Secur., vol. 55, pp. 21–45, 2015.

      [20] S. Uma Maheswari and D. Jude Hemanth, “Performance enhanced image steganography systems using transforms and optimization techniques,†Multimed. Tools Appl., vol. 76, no. 1, pp. 415–436, 2017.

      [21] T. Padmapriya, V.Saminadan, “Performance Improvement in long term Evolution-advanced network using multiple imput multiple output techniqueâ€, Journal of Advanced Research in Dynamical and Control Systems, Vol. 9, Sp-6, pp: 990-1010, 2017.

      [22] S.V.Manikanthan and K.Baskaran “Low Cost VLSI Design Implementation of Sorting Network for ACSFD in Wireless Sensor Networkâ€, CiiT International Journal of Programmable Device Circuits and Systems, Print: ISSN 0974 – 973X & Online: ISSN 0974 – 9624, Issue: November 2011, PDCS112011008.

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    MK, S. (2018). An Image Steganography using Particle Swarm Optimization and Transform Domain. International Journal of Engineering & Technology, 7(2.24), 474-477. https://doi.org/10.14419/ijet.v7i2.24.12139