DNA‑Enhanced Dual‑Layer Encryption and LSB Steganography for Data Security

Background: This paper proposes a practical dual-layer framework that combines dynamic DNA-indexed block substitution with a DNA-guided bidirectional LSB embedding to protect small secret payloads (text, small images, short audio) within cover images. Methods: A session-unique S-box is generated from a DNA subsequence and a cryptographically secure PRNG, producing per-session substitution and pixel transposition; the hiding stage embeds the resulting ciphertext using forward/backward indices (FIndex/LIndex) driven by nucleotide patterns (A, T, G, C). The system was implemented in C# (.NET 4.6.2) and evaluated on standard and medical image sets (cover sizes 256–1024) at payloads up to 0.25 bpp. Results: Results show strong encryption robustness (NPCR = 99.70%, UACI = 33.2%, entropy ≈ 7.98, adjacent-pixel correlation ≈ 0.015) and high stego imperceptibility (average PSNR ≈ 43.5 dB), while runtime remains practical (≈0.95 s to encrypt a 512×512 image; embedding ≈0.3 s). Comparisons against classical baselines (AES-128, 3DES, standard LSB) demonstrate comparable or improved diffusion and perceptual quality. We also present a security analysis, discuss limitations (computational cost, scalability, steganalysis coverage), and outline prioritized future work, including steganalysis testing, formal S-box analysis, optimization, and public code release to ensure reproducibility. Conclusion: The proposed approach offers a balanced trade-off between confidentiality and concealment for sensitive small payloads in realistic settings.

Authors

Publication Details

Journal
Israa University Journal for Applied Science
Published
2025-09-22
DOI
https://doi.org/10.52865/lkek6825
Primary Topic
DNA and Biological Computing
Type
article
Field-Weighted Citation Impact
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article

DNA‑Enhanced Dual‑Layer Encryption and LSB Steganography for Data Security

Mohammed Abbas Fadhil Al-Husainy, Ghayth Al-Asad, Mohammad Bani-Hani, Ala’eddin Al-Zu’bi et al.
Israa University Journal for Applied Science
DNA and Biological Computing
article

DNA‑Enhanced Dual‑Layer Encryption and LSB Steganography for Data Security

Mohammed Abbas Fadhil Al-Husainy, Ghayth Al-Asad, Mohammad Bani-Hani, Ala’eddin Al-Zu’bi, Sara Albatienh, Hazem Abuoliem
article en

Abstract

Background: This paper proposes a practical dual-layer framework that combines dynamic DNA-indexed block substitution with a DNA-guided bidirectional LSB embedding to protect small secret payloads (text, small images, short audio) within cover images. Methods: A session-unique S-box is generated from a DNA subsequence and a cryptographically secure PRNG, producing per-session substitution and pixel transposition; the hiding stage embeds the resulting ciphertext using forward/backward indices (FIndex/LIndex) driven by nucleotide patterns (A, T, G, C). The system was implemented in C# (.NET 4.6.2) and evaluated on standard and medical image sets (cover sizes 256–1024) at payloads up to 0.25 bpp. Results: Results show strong encryption robustness (NPCR = 99.70%, UACI = 33.2%, entropy ≈ 7.98, adjacent-pixel correlation ≈ 0.015) and high stego imperceptibility (average PSNR ≈ 43.5 dB), while runtime remains practical (≈0.95 s to encrypt a 512×512 image; embedding ≈0.3 s). Comparisons against classical baselines (AES-128, 3DES, standard LSB) demonstrate comparable or improved diffusion and perceptual quality. We also present a security analysis, discuss limitations (computational cost, scalability, steganalysis coverage), and outline prioritized future work, including steganalysis testing, formal S-box analysis, optimization, and public code release to ensure reproducibility. Conclusion: The proposed approach offers a balanced trade-off between confidentiality and concealment for sensitive small payloads in realistic settings.

Israa University Journal for Applied ScienceVol. 8(2)
Openalex Percentile: Top 77%
DNA and Biological Computing
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DNA‑Enhanced Dual‑Layer Encryption and LSB Steganography for Data Security — Mohammed Abbas Fadhil Al-Husainy, Ghayth Al-Asad, et al. · Israa University Journal for Applied Science (2025) | TGRS Research Map | TGRS