Skip to main content
SpringerLink
Log in

Secure visual communication with advanced cryptographic and ımage processing techniques

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

Abstract

Securing data during transmission is critical to prevent unauthorized access, interception, or modification of the data. Data can be communicated securely while maintaining its confidentiality, integrity, and availability by using cryptographic algorithms and measures. In the proposed work, a hybrid data compression algorithm is proposed to increase the amount of input data that is encrypted using the Advanced Encryption Standard (AES) cryptography method to boost security level, and it can be utilized to carry out the lossy compacting Steganography method. By reducing the quantity of data transmitted, this technique can enable speedy transmission over a sluggish internet connection or use less space on different storage devices. The cover image is compressed using Discrete Wavelet Transform (DWT), which reduces the cover image's dimensions by lossyly compressing the image. The ordinary text is converted to hexadecimal format from text. The encrypted data will then be inserted into the compressed cover picture using the least significant bit (LSB) with Image vector array (IVA). Bits per pixel (BPP), Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR), and Structural Similarity Index (SSIM) were some of the metrics we used to evaluate the proposed technique.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data availability

Data sharing not applicable to this article as no datasets were generated or analysed during the current study. No custom algorithm is used.

Abbreviations

AES:

Advanced encryption standard

DWT:

Discrete wavelet transform

LSB:

Least significant bit

IVA:

Image vector array

DES:

Data encryption standard

ECC:

Elliptic curve cryptography

SSIM:

Structural similarity ındex measure

PSNR:

Peak Signal-to-Noise Ratio

MSE:

Mean square error

BPP:

Bits per pixel

FED:

Fuzzy edge detection

EMD:

Exploiting modification direction

HVS:

Human visual system

DCT:

Discrete cosine transform

BTC:

Block truncation coding

PZMs:

Pseudo-Zernike moments

QKD:

Quantum key distribution

RSA:

Rivest–Shamir–Adleman

PKI:

Public key ınfrastructure

S-box:

Substitution box

RPE:

Redundant pattern encoding

SVD:

Singular value decomposition

3D DWT:

Three-dimensional discrete wavelet transform

PIM:

Processing-In Memory

AESPIM:

Architecture dubbed PIM

LBP:

Local binary pattern

PPM:

Pixel pair matching

ECC:

Elliptic curve cryptography

PCNG:

Pseudo-Chaotic Number Generator

PRNG:

Pseudo-Random Number Generator

ACRs:

Affine covariant regions

AMBTC:

Absolute moment block truncation coding

ZMs:

Zernike moments

References

  1. Dhargupta S, Chakraborty A, Ghosal SK, Saha S, Sarkar R (2019) Fuzzy edge detection based steganography using modifed Gaussian distribution. Multimed Tools Appl. https://doi.org/10.1007/s11042-018-7123-x

    Article  Google Scholar 

  2. Shen SY, Huang LH, Yu SS (2018) A novel adaptive data hiding based on improved EMD and interpolation. Multimed Tools Appl 77:131–141

    Article  Google Scholar 

  3. Saha S, Chakraborty A, Chatterjee A, Dhargupta S, Ghosal SK, Sarkar R (2020) Extended exploiting modifcation direction based steganography using hashed-weightage array. Multimed Tools Appl 79:20973–20993

    Article  Google Scholar 

  4. Chaı X, Haıyang Wu, Gan Z, Zhang Y, Chen Y, Nıxon KW (2020) An efficient visually meaningful image compression and encryption scheme based on compressive sensing and dynamıc Lsb embeddıng. Opt Lasers Eng 124:105837. https://doi.org/10.1016/J.Optlaseng.2019.105837

    Article  Google Scholar 

  5. Kharı M, Garg AK, Gandomı AH, Gupta R, Patan R, Balusamy B (2020) Securıng data ın Internet Of Thıngs (Iot) usıng cryptography and steganography technıques. IEEE Trans Syst Man Cybern Syst 50(1):73–80. https://doi.org/10.1109/Tsmc.2019.2903785

    Article  Google Scholar 

  6. Jeromel A, Žalık B (2020) An efficient lossy cartoon image compression method. Multımed Tools Appl 79:433–451. https://doi.org/10.1007/S11042-019-08126-7

    Article  Google Scholar 

  7. Bhardwaj M, Singh L, Saini KK (2019) An efficient approach to ınformation hiding through ımage steganography using edge detection, 4th International Conference on Information Systems and Computer Networks (ISCON), Mathura, India

  8. Shashi RK, Pavithra G, Manjunath TC (2022) Developing a novel steganography concept of audio data into audio streams. Int Conf Smart Syst Invent Technol (ICSSIT), 229–233. https://doi.org/10.1109/ICSSIT53264.2022.9716566

  9. Li W, Lin CC, Pan JS (2016) Novel image authentication scheme with fine image quality for BTC-based compressed images. Multimed Tools Appl 75:4771–4793. https://doi.org/10.1007/s11042-015-2502-z

  10. Chenthara S, Ahmed K, Wang H, Whittaker F (2019) Security and privacy-preserving challenges of e-health solutions in cloud computing. IEEE Access 7:74361–74382

    Article  Google Scholar 

  11. Ahmed N, Natarajan T, Rao KR (1974) Discrete cosine transform. IEEE Transact Comput C–23(1):90–93. https://doi.org/10.1109/T-C.1974.223784

    Article  MathSciNet  Google Scholar 

  12. Bartolini F, Tefas A, Barni M, Pitas I (2001) Image authentication techniques for surveillance applications. IEEE 89(10):1403–1418. https://doi.org/10.1109/5.959338

    Article  Google Scholar 

  13. Ramamurthi B, Gersho A (1986) Nonlinear space-variant postprocessing of block coded images. IEEE Trans Acoust Speech Signal Process 34(5):1258–1268. https://doi.org/10.1109/TASSP.1986.1164961

    Article  Google Scholar 

  14. Xin Y, Liao S, Pawlak M (2007) Circularly orthogonal moments for geometrically robust image watermarking. Pattern Recogn 40:3740–3752. https://doi.org/10.1016/j.patcog.2007.05.004

    Article  Google Scholar 

  15. Gao X, Deng C, Li X, Tao D (2010) Geometric distortion insensitive image watermarking in affine covariant regions. IEEE Trans Syst Man Cybern C 40:278–286. https://doi.org/10.1109/TSMCC.2009.2037512

    Article  Google Scholar 

  16. Haralick R, Sternberg S, Zhuang X (1987) Image analysis using mathematical morphology. Pattern analysis and machine ıntelligence. IEEE Trans Pattern Anal Mach Intell PAMI-9:532–550. https://doi.org/10.1109/TPAMI.1987.4767941

    Article  Google Scholar 

  17. Lema D, Mitchell O (1984) Absolute moment block truncation coding and its application to color images. IEEE Trans Commun 32:1148–1157. https://doi.org/10.1109/TCOM.1984.1095973

    Article  Google Scholar 

  18. Zhang X, Wang S, Qian Z, Feng G (2011) Self-embedding watermark with flexible restoration quality. Multimedia Tools Appl 54:385–395. https://doi.org/10.1007/s11042-010-0541-z

    Article  Google Scholar 

  19. Ravichandran D, Ahamad, M, Dhivakar M (2016) Performance analysis of three-dimensional medical image compression based on discrete wavelet transform. In: 22nd International Conference on Virtual System & Multimedia (VSMM), pp 1–8. https://doi.org/10.1109/VSMM.2016.7863176

  20. ZainEldin H, Elhosseini MA, Ali HA (2015) Image compression algorithms in wireless multimedia sensor networks: a survey. Ain Shams Eng J 6(2):481–490

    Article  Google Scholar 

  21. Thanki RM, Kothari A (2019) Data compression and ıts applicationin medical ımaging. In: Hybrid and advanced compression techniques for medical images, pp 1–15. https://link.springer.com/chapter/10.1007/978-3-030-12575-2_1

  22. Liu Y, Wang L, Qouneh A, Xin Fu (2022) Enabling PIM-based AES encryption for online video streaming. J Syst Architect 132(2022):102734. https://doi.org/10.1016/j.sysarc.2022.102734

    Article  Google Scholar 

  23. Chakraborty S, Jalal AS (2020) A novel local binary pattern based feature image steganography. Multimed Tools Appl 79:19561–19574

    Article  Google Scholar 

  24. Arivazhagan S, Sylvia Lilly Jebarani W, Ananthi Roy S, Amrutha E (2019) Improving quality of stego images through dithering techniques for pixel pair matching steganographic schemes. Int J Eng Adv Technol (IJEAT) 8(6):4923–4931. https://doi.org/10.35940/ijeat.F9239.088619

    Article  Google Scholar 

  25. Amrutha E, ArivazhaganJebarani SWSL (2022) Novel color image steganalysis method based on RGB channel empirical modes to expose stego images with diverse payloads. Pattern Anal Appl 26(1):239–253. https://doi.org/10.1007/s10044-022-01102-2

    Article  Google Scholar 

  26. Duan D, Guo N, Lıu B, Lı MG, Qın C (2020) A new hıgh capacıty ımage steganography method combıned wıth ımage ellıptıc curve cryptography and deep neural network. IEEE Access 8:25777–25788. https://doi.org/10.1109/Access.2020.2971528

    Article  Google Scholar 

  27. Qiao Z, El Assad S, Taralova I (2020) Design of secure cryptosystem based on chaotic components and AES S-Box. AEU – Int J Electron Commun 121:153205. https://doi.org/10.1016/j.aeue.2020.153205

    Article  Google Scholar 

  28. Ajish S, AnilKumar KS (2021) Secure mobile internet voting system using biometric authentication and wavelet based AES. J Inform Secur Appl 61:102908. https://doi.org/10.1016/j.jisa.2021.102908

    Article  Google Scholar 

  29. Bennett C, Brassard G (2020) Quantum cryptography: public key distribution and coin tossing. Theor Comput Sci - TCS 560:175–179. https://doi.org/10.1016/j.tcs.2011.08.039

    Article  Google Scholar 

  30. Grzywak A, Pilch-Kowalczyk G (2009) Quantum cryptography: opportunities and challenges. In: Tkacz E, Kapczynski A (eds) Internet – technical development and applications. Advances in intelligent and soft computing, vol 64. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05019-0_22

  31. Sari A, Ardiansyah G, Rachmawanto E, Setiadi DRIM (2019) An improved security and message capacity using AES and Huffman coding on image steganography. TELKOMNIKA Indones J Electr Eng 17:2400–2409. https://doi.org/10.12928/TELKOMNIKA.v17i5.9570

    Article  Google Scholar 

  32. Wahab OFA, Khalaf AAM, Hussein AI, Hamed HFA (2021) Hiding data using efficient combination of RSA cryptography, and compression steganography techniques. IEEE Access 9:31805–31815. https://doi.org/10.1109/ACCESS.2021.3060317.F

    Article  Google Scholar 

  33. Sharma N, Batra U (2018) Performance analysis of compression algorithms for information security: a review. ICST Trans Scalable Inf Syst 7(27):163503

    Article  Google Scholar 

  34. Dehshiri M, Sabouri SG, Khorsandi A (2021) Structural similarity assessment of an optical coherence tomographic image enhanced using the wavelet transform technique. J Opt Soc Amer A Opt Image Sci 38(1):1–9

    Article  Google Scholar 

Download references

Funding

No funds, grants, or other support was received.

Author information

Authors and Affiliations

  1. Mepco Schlenk Engineering College, Sivakasi, India

    V. Sathananthavathi, K. Ganesh Kumar & M. Sathish Kumar

Authors
  1. V. Sathananthavathi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K. Ganesh Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. Sathish Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Sathananthavathi, Ganesh kumar and Sathish kumar. The first draft of the manuscript was written by Sathananthavathi and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to V. Sathananthavathi.

Ethics declarations

Conflict of interest

Nil.

Additional information

Publisher's note

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

Appendix

Appendix

Figure 6

Fig. 6
figure 6

AES—basic working methodology

Full size image

Figure 7

Fig. 7
figure 7

AES with 256-bit key

Full size image

Figure 8

Fig. 8
figure 8

Discrete wavelet transform

Full size image

Figure 9

Fig. 9
figure 9

LSB embedding methodology

Full size image

Figure 10

Fig. 10
figure 10

LSB embedding process

Full size image

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

Sathananthavathi, V., Ganesh Kumar, K. & Sathish Kumar, M. Secure visual communication with advanced cryptographic and ımage processing techniques. Multimed Tools Appl 83, 45367–45389 (2024). https://doi.org/10.1007/s11042-023-17224-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-023-17224-6

Keywords

Search

Navigation