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<p>High Efficiency Video Coding (H.265/HEVC) offers a wide range of Intra-Prediction Modes (IPMs), presenting a valuable opportunity to increase embedding capacity in IPM-based video steganography. A central challenge in this domain lies in establishing a robust and secure mapping between secret data and the available IPMs. However, existing IPM-based steganographic methods for HEVC often overlook two fundamental characteristics of HEVC streams: the spatial correlation of IPMs and the transfer probabilities of IPMs during re-compression. Neglecting these aspects compromises the methods’ resilience, rendering them vulnerable to both statistical and calibration-based steganalysis. In this study, we propose a secure and efficient steganographic scheme that explicitly incorporates both the spatial correlation and transfer dynamics of IPMs to enhance resistance against steganalytic attacks. We conduct a comprehensive analysis of the distribution patterns and spatial correlations of IPMs in HEVC streams, which informs a cover elements selection strategy designed to minimize detectable anomalies. Furthermore, we introduce a mapping mechanism that anticipates IPMs alterations caused by re-compression, thereby preserving the statistical integrity of the IPMs distribution. Extensive experimental evaluations demonstrate that the proposed approach outperforms several state-of-the-art techniques across key performance dimensions, including anti-steganalysis resilience, coding efficiency, perceptual quality, and computational complexity.</p>

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Secure HEVC video steganography using IPMs spatial distribution and transfer probability

  • 期刊论文

  • 发表日期：

    2026年1月22日

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  • Ramadhani R. Iddy,
  • Gaobo Yang,
  • Dewang Wang,
  • Xiangling Ding,
  • Senzota K. Semakuwa

摘要

High Efficiency Video Coding (H.265/HEVC) offers a wide range of Intra-Prediction Modes (IPMs), presenting a valuable opportunity to increase embedding capacity in IPM-based video steganography. A central challenge in this domain lies in establishing a robust and secure mapping between secret data and the available IPMs. However, existing IPM-based steganographic methods for HEVC often overlook two fundamental characteristics of HEVC streams: the spatial correlation of IPMs and the transfer probabilities of IPMs during re-compression. Neglecting these aspects compromises the methods’ resilience, rendering them vulnerable to both statistical and calibration-based steganalysis. In this study, we propose a secure and efficient steganographic scheme that explicitly incorporates both the spatial correlation and transfer dynamics of IPMs to enhance resistance against steganalytic attacks. We conduct a comprehensive analysis of the distribution patterns and spatial correlations of IPMs in HEVC streams, which informs a cover elements selection strategy designed to minimize detectable anomalies. Furthermore, we introduce a mapping mechanism that anticipates IPMs alterations caused by re-compression, thereby preserving the statistical integrity of the IPMs distribution. Extensive experimental evaluations demonstrate that the proposed approach outperforms several state-of-the-art techniques across key performance dimensions, including anti-steganalysis resilience, coding efficiency, perceptual quality, and computational complexity.