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<p>Secure data transmission within digital images remains a critical challenge due to vulnerabilities to key interception and steganalysis attacks. Traditional steganographic schemes often require shared keys, pre-trained models, or prior coordination, which limits their practical deployment in open environments without prior synchronization or shared secrets. This paper introduces a symmetric dual-key encryption-steganography hybrid, inspired by one-time pad (OTP) principles, that enables secure image-based communication without any key exchange or prior shared knowledge. The method achieves high secrecy and imperceptibility, embedding hidden data without introducing visible distortions or statistical artifacts. The approach is lightweight, general, and does not depend on training or image-specific assumptions. Experimental validation on 100 natural images demonstrates strong resilience to advanced steganalysis, high visual quality (SSIM &gt; 0.97, PSNR &gt; 40 dB), and secure hidden data transmission. These results highlight the method’s practical value as a robust and transparent solution for sensitive image-based communication, without the limitations of prior coordination or machine learning infrastructure.</p>

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A secure encryption-steganography method for public images using symmetric keys without prior synchronization

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月31日

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  • Yosef Golovachev,
  • Ephraim Ashush,
  • Benjamin Milgrom

摘要

Secure data transmission within digital images remains a critical challenge due to vulnerabilities to key interception and steganalysis attacks. Traditional steganographic schemes often require shared keys, pre-trained models, or prior coordination, which limits their practical deployment in open environments without prior synchronization or shared secrets. This paper introduces a symmetric dual-key encryption-steganography hybrid, inspired by one-time pad (OTP) principles, that enables secure image-based communication without any key exchange or prior shared knowledge. The method achieves high secrecy and imperceptibility, embedding hidden data without introducing visible distortions or statistical artifacts. The approach is lightweight, general, and does not depend on training or image-specific assumptions. Experimental validation on 100 natural images demonstrates strong resilience to advanced steganalysis, high visual quality (SSIM > 0.97, PSNR > 40 dB), and secure hidden data transmission. These results highlight the method’s practical value as a robust and transparent solution for sensitive image-based communication, without the limitations of prior coordination or machine learning infrastructure.