Font-Based Text Steganography for Covert Communication in Devanagari Script: A Review (2020–2026)

Year : 2026 | Volume : 03 | Issue : 02 | Page : 22 33
By

Mohd Kamil,

Hitesh Singh,

Aditee Mattoo,

  1. Student, Department of Computer Science and Engineering, Noida Institute of Engineering and Technology, Greater Noida, Uttar Pradesh, India
  2. Student, Department of Computer Science and Engineering, Noida Institute of Engineering and Technology, Greater Noida, Uttar Pradesh, India
  3. Assistant Professor, Department of Computer Science and Engineering, Noida Institute of Engineering and Technology, Greater Noida, Uttar Pradesh, India

Abstract

Steganography hides the fact that a communication exists rather than merely safeguarding its content. Text is the most challenging of all steganographic media because it contains the least redundancy and is the most sensitive to changes. Devanagari script, with its conjunct consonants, ligatures, matras, and non-linear glyph construction, makes these difficulties even harder, rendering rendering-dependent and OCR- based steganographic methods largely ineffective. This paper presents a systematic review of text steganography, with particular focus on font- based approaches and their applicability to Devanagari script, covering the period 2020 to 2026. The review classifies methods into six broad categories linguistic, format-based, Unicode-based, OCR-based, glyph- perturbation, font-metadata, and LLM-generative and analyses them across capacity, imperceptibility, robustness, determinism, and script awareness. A key finding is that despite the widespread digital use of Indic languages, virtually no high-capacity text steganography system addresses the structural complexity of Devanagari. Font-internal encoding specifically the use of font metadata tables in TrueType/OpenType fonts emerges as the most promising approach for achieving deterministic, OCR-free, and script-aware covert communication in Devanagari. The review outlines open challenges, evaluates existing methods against a unified metrics framework, and proposes future research directions including multi-script font systems, GAN-based glyph generation, hybrid semantic-visual encoding, and standardised Indic benchmarks.

Keywords: Text steganography, font-based steganography, covert communication, Devanagari script, glyph perturbation, font meta- data, Indic script steganography, OCR-free encoding, linguistic steganography.

[This article belongs to Emerging Trends in Languages ]

How to cite this article: Mohd Kamil, Hitesh Singh, Aditee Mattoo. Font-Based Text Steganography for Covert Communication in Devanagari Script: A Review (2020–2026). Emerging Trends in Languages. 2026; 03(02):22-33.
How to cite this URL: Mohd Kamil, Hitesh Singh, Aditee Mattoo. Font-Based Text Steganography for Covert Communication in Devanagari Script: A Review (2020–2026). Emerging Trends in Languages. 2026; 03(02):22-33. Available from: https://journals.stmjournals.com/etl/article=2026/view=254136

References

  1. Rani N, Chaudhary J. Text steganography techniques: A review. International Journal of Engineering Trends and Technology (IJETT). 2013 Jul;4(7):3013-3015.
  2. Liu A, Pan L, Lu Y, Li J, Hu X, Zhang X, Wen L, King I, Xiong H, Yu P. A survey of text watermarking in the era of large language models. ACM Computing Surveys. 2024 Nov 7;57(2):1-36.
  3. Majeed MA, Sulaiman R, Shukur Z, Hasan MK. A review on text steganography techniques. Mathematics. 2021 Nov 8;9(21):2829.
  4. Al-Ghaili AM, Kasim H, Hassan Z, Al-Hada NM, Othman M, Kasmani RM, Shayea I. A review: image processing techniques’ roles towards energy-efficient and secure iot. Applied sciences. 2023 Feb 6;13(4):2098.
  5. Ahvanooey MT, Zhu MX, Li Q, Mazurczyk W, Choo KK, Gupta BB, Conti M. Modern authentication schemes in smartphones and IoT devices: An empirical survey. IEEE Internet of Things Journal. 2021 Dec 24;9(10):7639-63.
  6. Vishwanath NV, Manjunathachari K, Prasad KS. Multi-lingual character segmentation and recognition based on adaptive projection profiles and composite feature vectors. Multimedia Tools and Applications. 2023 Jul;82(16):24247-68.
  7. Xiao C, Zhang C, Zheng C. Fontcode: Embedding information in text documents using glyph perturbation. ACM Transactions on Graphics (TOG). 2018 Feb 28;37(2):1-6.
  8. Simmons GJ. The prisoners’ problem and the subliminal channel. In Advances in Cryptology: Proceedings of Crypto 83 1984 Aug 22 (pp. 51-67). Boston, MA: Springer US.
  9. Li S, Wang J, Liu P. Detection of generative linguistic steganography based on explicit and latent text word relation mining using deep learning. IEEE Transactions on Dependable and Secure Computing. 2022 Mar 10;20(2):1476-87.
  10. Yang ZL, Zhang SY, Hu YT, Hu ZW, Huang YF. VAE-Stega: Linguistic Steganography based on variational autoencoder. IEEE Transactions on Information Forensics and Security. 2020 Sep 10; 16:880-95.
  11. Zhou X, Peng W, Yang B, Wen J, Xue Y, Zhong P. Linguistic steganography based on adaptive probability distribution. IEEE Transactions on Dependable and Secure Computing. 2021 May 13;19(5):2982-97.
  12. Alanazi N, Khan E, Gutub A. Involving spaces of unicode standard within irreversible Arabic text steganography for practical implementations. Arabian Journal for Science and Engineering. 2021 Sep;46(9):8869-85.
  13. Lin K, Luo Y, Zhang Z, Ping L. Zero-shot generative linguistic steganography. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) 2024 Jun (pp. 5168-5182).
  14. Yang B, Peng W, Xue Y, Zhong P. A Generation-based Text Steganography by Maintaining Consistency of Probability Distribution. KSII Trans. Internet Inf. Syst. 2021 Nov 1;15(11):4184-202.
  15. Cao Y, Zhou Z, Chakraborty C, Wang M, Wu QJ, Sun X, Yu K. Generative steganography based on long readable text generation. IEEE transactions on computational social systems. 2022 May 19;11(4):4584-94.
  16. Zhang Z, Wen J, Gao L, Peng W, Xue Y. Linguistic steganalysis based on few-shot adversarial training. IEEE Transactions on Dependable and Secure Computing. 2025 Jan 22;22(4):3514-28.
  17. KL SN, R BK. Text steganography: enhanced character-level embedding algorithm using font attribute with increased resilience to statistical attacks. Multimedia Tools and Applications. 2025 Mar;84(11):9367-92.
  18. Meng J, Lu Z. Advances in Semantic-Preserving Text Watermarking. Sensors. 2026 Feb 28;26(5):1528.
  19. Ji Y, Cao J, Li Q, Liu Y, Wei T, Xu K, Wu J. Constructing SDN covert timing channels between hosts with unprivileged attackers. IEEE Transactions on Networking. 2024 Nov 20;33(2):612-23.
  20. Petitcolas FA, Anderson RJ, Kuhn MG. Information hiding-a survey. Proceedings of the IEEE. 1999 Jul 31;87(7):1062-78.
  21. Yang ZL, Guo XQ, Chen ZM, Huang YF, Zhang YJ. RNN-stega: Linguistic steganography based on recurrent neural networks. IEEE Transactions on Information Forensics and Security. 2018 Sep 24;14(5):1280-95.
  22. Tran TM, Vu TN, Vo ND, Nguyen TV, Nguyen K. Anomaly analysis in images and videos: A comprehensive review. ACM Computing Surveys. 2022 Dec 15;55(7):1-37.
Regular Issue Subscription Original Research
Volume 03
Issue 02
Received 29/06/2026
Accepted 09/07/2026
Published 10/07/2026
Publication Time 11 Days

Login

My IP

PlumX Metrics