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RI-CDVS: Robust and Imperceptible Compressed Domain Video Steganography Using H.265 Codec

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Abstract

The development of steganography methods has raised growing worries about steganography abuse. As the significant demand for digital video processing is on the rise from last decade, data security becomes a crucial issue. Motion vector manipulation (MVM)-based video steganography has caught attention since it can result in indirect and arbitrary alterations in video data. The moderate payload capacity and complexity are issues faced by MV-based methods. A hybrid motion estimation and transform coefficients strategy applied on video steganography using the H.265 compression method is proposed. The robust imperceptible compressed domain video steganography (RI-CDVS) model is presented to increase imperceptibility with improved security. The two phases of the RI-CDVS model are embedding and extraction. The embedding stage generates the compressed stego video from the inputs of compressed cover video and secret image. Using dynamic threshold from the cover video, the motion estimation technique is used to select the group of key frames. The key frames are chosen to hide the secret image without sacrificing quality and lower error rate. The Discrete Cosine Transform (DCT) is used to transform keyframes into the frequency domain. The Least Significant Bit (LSB) of the integer coefficients of the DCT components is used to embed the secret information. The H.265 codec is used to create the compressed stego video. At extraction phase reverse operations are performed to get secret image. The experiments are conducted using a publicly accessible video collection and compared the results of RICDVS with the techniques at the cutting edge of video steganography.

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Data availability

The datasets used during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Authors and Affiliations

  1. Instrumentation Engineering, R.A.I.T., Navi Mumbai, India

    Shamal Salunkhe

  2. Electrical Engineering, V.J.T.I., Mumbai, India

    Surendra Bhosale

Authors
  1. Shamal Salunkhe
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  2. Surendra Bhosale
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Correspondence to Shamal Salunkhe.

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This article is part of the topical collection “Enabling Innovative Computational Intelligence Technologies for IOT” guest edited by Omer Rana, Rajiv Misra, Alexander Pfeiffer, Luigi Troiano and Nishtha Kesswani.

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Salunkhe, S., Bhosale, S. RI-CDVS: Robust and Imperceptible Compressed Domain Video Steganography Using H.265 Codec. SN COMPUT. SCI. 4, 357 (2023). https://doi.org/10.1007/s42979-023-01681-9

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  • DOI: https://doi.org/10.1007/s42979-023-01681-9

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