Skip to main content

Advertisement

Log in

Developing an adaptive DCT-based steganography method using a genetic algorithm

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Steganography is an appropriate approach to establish a secure connection between the sender and the receiver. Data embedding in Discrete Cosine Transform (DCT) coefficients for JPEG images is one of the most practical approaches nowadays. In this paper, a new method called GA-Shield is proposed, in which, instead of using fixed embedding capacity, embedding a different number of bits in the quantized DCT coefficients according to the magnitude of the coefficient is used to spread bits of secret message in the most suitable coefficients. In addition, this method uses a genetic algorithm to minimize the distortion due to embedding. This minimization is performed by deciding on the best formula to calculate coefficient value after embedding. In this phase, PSNR is used as the metric to measure the amount of distortion in the cover image to produce the stego image. As these changes decrease, the value of PSNR would be optimized, and the stego image would have better quality. The proposed method can embed 300 to 20,000 bits of data (on average) in the cover image and produce the stego image with a PSNR value in the range of 65 to 40 and a SSIM value of more than 0.985. The consequences of comparisons with the state-of-the-art show that despite the fact that the proposed technique has less embedding capacity than some of the current ones, the superiority of stego image quality and security of the proposed technique, mainly at low embedding levels, is significant.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Algorithm 1
Algorithm 2
Algorithm 3
Algorithm 4
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data availability

Not applicable.

Code availability

Not applicable.

References

  1. Abdulla AA, Jassim SA, Sellahewa H (2013) Secure steganography technique based on bitplane indexes. In: Proc. - 2013 IEEE Int Symp Multimedia, ISM 2013, pp. 287–291. https://doi.org/10.1109/ISM.2013.55

  2. Abdulla AA, Sellahewa H, Jassim SA (2014) Steganography based on pixel intensity value decomposition. 9120:19–27. https://doi.org/10.1117/12.2050518

  3. Abdulla AA, Sellahewa H, Jassim SA (2019) Improving embedding efficiency for digital steganography by exploiting similarities between secret and cover images. Multimed Tools Appl 78(13):17799–17823. https://doi.org/10.1007/S11042-019-7166-7

    Article  Google Scholar 

  4. Attaby AA, Mursi Ahmed MFM, Alsammak AK (2018) Data hiding inside JPEG images with high resistance to steganalysis using a novel technique: DCT-M3. Ain Shams Eng J 9(4):1965–1974. https://doi.org/10.1016/J.ASEJ.2017.02.003

    Article  Google Scholar 

  5. Banharnsakun A (2018) Artificial bee colony approach for enhancing LSB based image steganography. Multimed Tools Appl:77(20). https://doi.org/10.1007/s11042-018-5933-5.

  6. Bansal D, Chhikara R (2014) An improved DCT based steganography technique. Int J Comput Appl 102(14):46–49. https://doi.org/10.5120/17887-8861

    Article  Google Scholar 

  7. Baziyad M, Rabie T, Kamel I (2021) Toward stronger energy compaction for high capacity dct-based steganography: a region-growing approach. Multimed Tools Appl 80(6):8611–8637. https://doi.org/10.1007/S11042-020-10008-2

    Article  Google Scholar 

  8. Bhattacharyya S, Khan A, Sanyal G (2014) DCT Difference Modulation(DCTDM) Image Steganography. Int J Inf Netw Secur 3(1)40–63. Accessed 23 Dec 2021. [Online]. Available: http://iaesjournal.com/online/index.php/IJINS

  9. Biswas R, Bandyapadhay SK (2019) Random selection based GA optimization in 2D-DCT domain color image steganography. undefined 79(11–12):7101–7120. https://doi.org/10.1007/S11042-019-08497-X

    Article  Google Scholar 

  10. Chang CC, Chen TS, Chung LZ (2002) A steganographic method based upon JPEG and quantization table modification. Inf Sci (Ny) 141(1–2):123–138. https://doi.org/10.1016/S0020-0255(01)00194-3

    Article  MATH  Google Scholar 

  11. Chen ST, Huang HN, Kung WM, Hsu CY (2015) Optimization-based image watermarking with integrated quantization embedding in the wavelet-domain. undefined 75(10):5493–5511. https://doi.org/10.1007/S11042-015-2522-8

    Article  Google Scholar 

  12. Eggers JJ, Baeuml R, Girod B (2002) Communications approach to image steganography. In: Proc. SPIE 4675, security and watermarking of multimedia contents IV. https://doi.org/10.1117/12.465284

  13. Evsutin O, Kokurina A, Meshcheryakov R, Shumskaya O (2018) The adaptive algorithm of information unmistakable embedding into digital images based on the discrete Fourier transformation. Multimed Tools Appl 2018 7721 77(21):28567–28599. https://doi.org/10.1007/S11042-018-6055-9

    Article  Google Scholar 

  14. Evsutin O, Melman A, Meshcheryakov R (2021) Algorithm of error-free information embedding into the DCT domain of digital images based on the QIM method using adaptive masking of distortions. Signal Process 179:107811. https://doi.org/10.1016/J.SIGPRO.2020.107811

    Article  Google Scholar 

  15. Hou D, Wang H, Zhang W, Yu N (2018) Reversible data hiding in JPEG image based on DCT frequency and block selection. Signal Process 148:41–47. https://doi.org/10.1016/J.SIGPRO.2018.02.002

    Article  Google Scholar 

  16. Huang F, Qu X, Kim HJ, Huang J (2016) Reversible data hiding in JPEG images. IEEE Trans Circuits Syst Video Technol 26(9):1610–1621. https://doi.org/10.1109/TCSVT.2015.2473235

    Article  Google Scholar 

  17. Hussain M, Wahab AWA, Bin Idris YI, Ho ATS, Jung KH (2018) Image steganography in spatial domain: A survey. Signal Process Image Commun:65. https://doi.org/10.1016/j.image.2018.03.012.

  18. Jiang C, Pang Y, Xiong S (2013) A high capacity Steganographic method based on quantization table modification and F5 algorithm. Circuits, Syst Signal Process 33(5):1611–1626. https://doi.org/10.1007/S00034-013-9703-3

  19. Kadhim IJ, Premaratne P, Vial PJ (2020) Improved image steganography based on super-pixel and coefficient-plane-selection. Signal Process:171. https://doi.org/10.1016/j.sigpro.2020.107481.

  20. Kanan HR, Nazeri B (2014) A novel image steganography scheme with high embedding capacity and tunable visual image quality based on a genetic algorithm. Expert Syst Appl 41(14):6123–6130. https://doi.org/10.1016/J.ESWA.2014.04.022

    Article  Google Scholar 

  21. Kaur A, Kaur R, Kumar N (2016) Image steganography using Discrete Wavelet Transformation and Artificial Bee Colony Optimization. In: Proc. 2015 1st Int. Conf Next Gener Comput Technol NGCT 2015, pp 990–994. https://doi.org/10.1109/NGCT.2015.7375269

  22. Khamrui A, Gupta DD, Ghosh S, Nandy S (2017) A spatial domain image authentication technique using genetic algorithm. Commun Comput Inf Sci 776:577–584. https://doi.org/10.1007/978-981-10-6430-2_45

    Article  Google Scholar 

  23. Khan S, Bianchi T (2018) Ant colony optimization (ACO) based data hiding in image complex region. Int J Electr Comput Eng 8(1). https://doi.org/10.11591/ijece.v8i1.pp379-389

  24. Khan S et al (2019) On hiding secret information in medium frequency DCT components using least significant bits steganography. C – Comput Model Eng Sci 118(3):529–546. https://doi.org/10.31614/CMES.2019.06179

    Article  Google Scholar 

  25. Kumar KS, Raja KB, Chhotaray RK, Pattanaik S (2010) Bit length replacement steganography based on DCT coefficients. Int J Eng Sci Technol 2(8):3561–3570

  26. Lima R, Gramacho W, Henrique A (2017) Optimizing image steganography using particle swarm optimization algorithm. Int J Comput Appl 164(7):1–5. https://doi.org/10.5120/ijca2017913686

    Article  Google Scholar 

  27. McAteer I, Ibrahim A, Zheng G, Yang W, Valli C (2019) Integration of biometrics and steganography: a comprehensive review. Technol 7(2):34. https://doi.org/10.3390/TECHNOLOGIES7020034

    Article  Google Scholar 

  28. Melman A, Petrov P, Shelupanov A (2020) An adaptive algorithm for embedding information into compressed JPEG images using the QIM method. Accessed 23 Dec 2021. [Online]. Available: https://arxiv.org/abs/2012.08742v1

  29. Miri A, Faez K (2017) Adaptive image steganography based on transform domain via genetic algorithm. Optik (Stuttg) vol. 145. https://doi.org/10.1016/j.ijleo.2017.07.043

  30. MK S, MK S (2018) An image steganography using particle swarm optimization and transform domain. Int J Eng Technol 7(2.24):474–477. https://doi.org/10.14419/ijet.v7i2.24.12139

    Article  Google Scholar 

  31. Nipanikar SI, Hima Deepthi V, Kulkarni N (2018) A sparse representation based image steganography using Particle Swarm Optimization and wavelet transform. Alexandria Eng J 57(4). https://doi.org/10.1016/j.aej.2017.09.005

  32. Noda H, Niimi M, Kawaguchi E (2006) High-performance JPEG steganography using quantization index modulation in DCT domain. Pattern Recogn Lett 27(5):455–461. https://doi.org/10.1016/J.PATREC.2005.09.008

    Article  Google Scholar 

  33. Patel H, Dave P (2012) Steganography technique based on DCT coefficients. Int J Eng Res Appl 2(1):713–717. http://www.ijera.com

  34. Pevný T, Bas P, Fridrich J (2010) Steganalysis by subtractive pixel adjacency matrix. IEEE Trans Inf Forensics Secur 5(2). https://doi.org/10.1109/TIFS.2010.2045842

  35. Pramanik S, Singh RP, Ghosh R (2020) Application of bi-orthogonal wavelet transform and genetic algorithm in image steganography. Multimed Tools Appl 79(25–26). https://doi.org/10.1007/s11042-020-08676-1

  36. Roy R, Laha S (2015) Optimization of Stego image retaining secret information using genetic algorithm with 8-connected PSNR. Procedia Comput Sci 60(1):468–477. https://doi.org/10.1016/J.PROCS.2015.08.168

    Article  Google Scholar 

  37. Sabeti V, Ahmadi S (2020) Adaptive image steganography in the difference value of discrete cosine transform coefficients. J Soft Comput Inf Technol 9(3):55–66

    Google Scholar 

  38. Saidi M, Hermassi H, Rhouma R, Belghith S (2017) A new adaptive image steganography scheme based on DCT and chaotic map. Multimed Tools Appl 76(11):13493–13510. https://doi.org/10.1007/S11042-016-3722-6

    Article  Google Scholar 

  39. Sajid Ansari A, Sajid Mohammadi M, Tanvir Parvez M (2017) JPEG image steganography based on coefficients selection and partition. undefined 9(6):14–22. https://doi.org/10.5815/IJIGSP.2017.06.02

    Article  Google Scholar 

  40. Shah PD, Bichkar RS (2018) A secure spatial domain image steganography using genetic algorithm and linear congruential generator. Adv Intell Syst Comput 632:119–129. https://doi.org/10.1007/978-981-10-5520-1_12

    Article  Google Scholar 

  41. Tang W, Li B, Barni M, Li J, Huang J (2021) Improving cost learning for JPEG steganography by exploiting JPEG domain knowledge. IEEE Trans Circuits Syst Video Technol. https://doi.org/10.1109/TCSVT.2021.3115600

  42. Wang RZ, Lin CF, Lin JC (2001) Image hiding by optimal LSB substitution and genetic algorithm. Pattern Recogn 34(3):671–683. https://doi.org/10.1016/S0031-3203(00)00015-7

    Article  MATH  Google Scholar 

  43. Wazirali R, Alasmary W, Mahmoud MMEA, Alhindi A (2019) An optimized steganography hiding capacity and imperceptibly using genetic algorithms. IEEE Access:7. https://doi.org/10.1109/ACCESS.2019.2941440

  44. Wedaj FT, Kim S, Kim HJ, Huang F (2017) Improved reversible data hiding in JPEG images based on new coefficient selection strategy. Eurasip J Image Vid Process 2017(1):1–11. https://doi.org/10.1186/S13640-017-0206-1/TABLES/6

    Article  Google Scholar 

  45. Xiao M, Li X, Ma B, Zhang X, Zhao Y (2021) Efficient reversible data hiding for JPEG images with multiple histograms modification. IEEE Trans Circuits Syst Vid Technol 31(7):2535–2546. https://doi.org/10.1109/TCSVT.2020.3027391

    Article  Google Scholar 

  46. Xie J, Yang C, Huang D, Xie D (2008) A large capacity blind information hiding algorithm. Proc Int Symp Electron Commer Secur ISECS 2008:934–937. https://doi.org/10.1109/ISECS.2008.130

    Article  Google Scholar 

  47. Yu L, Zhao Y, Ni R, Zhu Z (2009) PM1 steganography in JPEG images using genetic algorithm. Soft Comput 4(13):393–400. https://doi.org/10.1007/S00500-008-0327-7

    Article  Google Scholar 

  48. Yu L, Zhao Y, Ni R, Zhu Z (2009) PM1 steganography in JPEG images using genetic algorithm. Soft Computing 13(4). https://doi.org/10.1007/s00500-008-0327-7

Download references

Funding

No funding was received to assist with the preparation of this manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Vajiheh Sabeti.

Ethics declarations

Conflict of interest

The authors have no financial or proprietary interests in any material discussed in this article.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sabeti, V., Aghabagheri, A. Developing an adaptive DCT-based steganography method using a genetic algorithm. Multimed Tools Appl 82, 19323–19346 (2023). https://doi.org/10.1007/s11042-022-14166-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-022-14166-3

Keywords

Navigation