A multi level image steganography methodology based on adaptive PMS and block based pixel swapping

  • Srilekha MukherjeeEmail author
  • Goutam Sanyal


The practice of information exchange through global media like internet extensively entails a security concern. This paper consists of a proposed approach that braces the security concern in the realm of image steganography. The adaptive technique of the Power Modulus Scrambling (PMS) has been preliminarily used so as to disturb the normal pixel orientation of the original carrier. A second layer of encryption is enforced with the implementation of the Block Based Pixel Swapping technique. These steps ensure a two tier secured shield. Next, the embedding procedure is facilitated depending on a comparative key based permutation combination methodology. This approach caters the need of security during communication. The proposed approach is evaluated with respect to substantial performance metrics. The commendable results obtained shows that the foothold of imperceptibility is well maintained.


Steganography Adaptive power Modulus scrambling Block based pixel swapping Peak signal to noise ratio Cross correlation coefficient 



  1. 1.
    Abdallah EE, Ben Hamza A, Bhattacharya P (2010) Video watermarking using wavelet transform and tensor algebra. SIViP 4:233–245CrossRefGoogle Scholar
  2. 2.
    Ahmad T, Abdullah M (2009) A novel steganographic method for gray-level images. World Acad Sci Eng Technol 3:574–579Google Scholar
  3. 3.
    Almohammad A, Ghinea G (2010) Stego-image quality and the reliability of PSNR. In: 2nd International Conference on Image Processing Theory Tools and Applications (IPTA), IEEE, pp 215–220Google Scholar
  4. 4.
    Alsmirat MA, Al-Alem F, Al-Ayyoub M et al (2018) Impact of digital fingerprint image quality on the fingerprint recognition accuracy. Multimed Tools Appl:1–40.
  5. 5.
    Atawneh S, Almomani A, Bazar HA, Sumari P, Gupta BB (2016) Secure and imperceptible digital image steganographic algorithm based on diamond encoding in DWT domain. Multimed Tools Appl 76:18451–18472CrossRefGoogle Scholar
  6. 6.
    Banerjee I, Indu P, Singh A et al (2015) Robust watermarking using four bit per pixel technique. Int J Electron Secur Digit Forensics 7:345–357Google Scholar
  7. 7.
    Bhattacharya S, Sanyal G (2010) A data hiding model with high security features combining finite state machines and PMM method. International Journal of Computer, Electrical, Automation, Control and Information Engineering 4:1243–1250Google Scholar
  8. 8.
    Chandramouli R, Kharrazi M, Memon N (2003) Image steganography and steganalysis concepts and practice. In: Kalker T, Cox IJ, Ro YM (eds) International workshop on digital watermarking (IWDW). Springer Verlag, Berlin, pp 35–49Google Scholar
  9. 9.
    Chang C et al (2002) A steganographic method based upon JPEG and quantization table modification. Inf Sci 141:123–138CrossRefGoogle Scholar
  10. 10.
    Das S, Muhammad K, Bakshi S et al (2018) Lip biometric template security framework using spatial steganography. Pattern Recogn Lett.
  11. 11.
    Dukkipati A (2012) On maximum entropy and minimum KL-divergence optimization by Gröbner basis methods. Appl Math Comput 218:11674–11687MathSciNetzbMATHGoogle Scholar
  12. 12.
    Elsheh E, Ben Hamza A (2011) Secret sharing approaches for 3D object encryption. Expert Syst Appl 38:13906–13911Google Scholar
  13. 13.
    Ferzli R, Girija L, Ali W (2010) Efficient implementation of kurtosis based no reference image sharpness metric. In: Astola J, Egiazarian KO (eds) Proceedings in Image Processing: Algorithms and Systems VIII, Volume 7532, SPIE, San Jose, CaliforniaGoogle Scholar
  14. 14.
    Gurav M, Mukesh Tiwari P, Singh P (2015) High secured image by LSB steganography technique using matlab. International Journal on Recent and Innovation Trends in Computing and Communication 3:1836–1840CrossRefGoogle Scholar
  15. 15.
    Huang P, Chang K, Chang C et al (2008) A novel image steganography method using tri-way pixel value differencing. J Multimed 3:37–44Google Scholar
  16. 16.
    Joshi R, Gagnani L, Pandey S (2013) Image steganography with LSB. Int J Adv Res Comput Eng Technol 2:228–229Google Scholar
  17. 17.
    Lan T, Mansour M, Tewfik A (2000) Robust high capacity Data embedding. In: International Conference on Image Processing (ICIP), Vancouver, BC, CanadaGoogle Scholar
  18. 18.
    Lundin R, Lindskog S (2012) An investigation of entropy of selectively encrypted bitmap images. In: Computational Aspects of Social Networks (CASoN), San Carlos, Brazil, pp 238–243Google Scholar
  19. 19.
    Luo W, Huang F, Huang J (2010) Edge adaptive image steganography based on LSB matching revisited. IEEE Trans Inf Forensics Secur 5:201–214CrossRefGoogle Scholar
  20. 20.
    Luo X et al (2012) On F5 steganography in images. Comput J 55Google Scholar
  21. 21.
    Maheswari SU, Hemanth DJ (2015) Performance enhanced image steganography systems using transforms and optimization techniques. Multimed Tools Appl 76:415–436Google Scholar
  22. 22.
    Mukherjee S, Sanyal G (2016) A novel image steganography methodology based on adaptive PMS technique. In: International Conference on Advanced Computing, Networking and Informatics (ICACNI 2016). Progress in Intelligent Computing Techniques: Theory, Practice, and Applications. Springer, Singapore, pp 157–164Google Scholar
  23. 23.
    Mukherjee S, Sanyal G (2017) Enhanced position power first mapping (PPFM) based image steganography. Int J Comput Appl 39:59–68Google Scholar
  24. 24.
    Mukherjee S, Sanyal G (2018) A chaos based image steganographic system. Multimed Tools Appl 77:27851–27876Google Scholar
  25. 25.
    Mukherjee S, Ash S, Sanyal G (2015) A novel image steganographic methodology by power modulus scrambling with logistic mapping. In: TENCON, IEEE Region 10 Conference, Macao, ChinaGoogle Scholar
  26. 26.
    Nguyen S, Chang CC, Shih TH (2018) Effective reversible image steganography based on rhombus prediction and local complexity. Multimed Tools Appl 77:26449–26467Google Scholar
  27. 27.
    Potdar V, Chang E (2004) Gray level modification steganography for secret communication. In: IEEE International Conference on Industrial Informatics, Berlin, Germany, p 355–368Google Scholar
  28. 28.
    Safarpour M, Charmi M (2016) Capacity enlargement of the PVD steganography method using the GLM technique. CoRR, abs/1601.00299Google Scholar
  29. 29.
    Sanchetti A (2012) Pixel value differencing image steganography using secret key. Int J Innov Technol Exploring Eng 2:2278–3075Google Scholar
  30. 30.
    Sheisi H, Mesgarian J, Rahmani M (2012) Steganography: Dct coefficient replacement method and compare with JSteg algorithm. International Journal of Computer and Electrical Engineering 4:458–462Google Scholar
  31. 31.
    Shojanazeri H, Adnan WAW, Ahmad SMS et al (2015) Authentication of images using Zernike moment watermarking. Multimed Tools Appl 76:577–606Google Scholar
  32. 32.
    Singh K (2014) A survey on image steganography techniques. Int J Comput Appl 97:10–20Google Scholar
  33. 33.
    Su Q, Wang G, Zhang X et al (2015) An improved color image watermarking algorithm based on QR decomposition. Multimed Tools Appl 76:707–729Google Scholar
  34. 34.
    Wang D, Chang CC, Liu Y et al (2015) Digital image scrambling algorithm based on chaotic sequence and decomposition and recombination of pixel values. International Journal of Network Security 17:322–327Google Scholar
  35. 35.
    Yang C, Weng C, Wang S et al (2008) Adaptive data hiding in edge areas of images with spatial LSB domain systems. IEEE Trans Inf Forensics Secur 3:488–497CrossRefGoogle Scholar
  36. 36.
    Yu C, Li J, Li X, Ren X, Gupta BB (2017) Four-image encryption scheme based on quaternion Fresnel transform, chaos and computer generated hologram. Multimed Tools Appl 77:4585–4608CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Computer Science and Engineering DepartmentNational Institute of TechnologyDurgapurIndia

Personalised recommendations