Steganography algorithm based on discrete cosine transform for data embedding into raw video streams

Rajesh, G; Nargunam, A. Shajin

doi:10.1049/ic.2013.0370

Cited by 7 publications

(5 citation statements)

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“…The performance of this method was measured using peak signal to noise ratio (PSNR) and mean squared error (MSE) using different videos and different message lengths. Compared to the method proposed by Rajesh and Nargunam [17], this method reduced the MSE and increased the PSNR values. Using video scene change detection a technique was proposed by Ramalingam and Isa [18] to hide a secret image within a video series.…”

Section: Introductionmentioning

confidence: 89%

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High capacity video hiding based on multi-resolution stationary wavelet transform and hybrid-matrix decomposition techniqueset Transform and hybrid-matrix decomposition techniques

et al. 2022

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Internet simplified digital data transferring. This data needs to be secured; so securing digital data becomes an important concern. Steganography provides security for data by inserting it into a cover and concealing it. In this paper, a steganography algorithm was introduced. This algorithm used the stationary wavelet transform (SWT) and اhybrid-matrix decomposition techniques, singular value decomposition (SVD) and QR factorization to conceal a video in another video. The algorithm performance was measured with reference to the peak signal to noise ratio (PSNR) and structural similarity index measure (SSIM) for the cover and the secret videos. The algorithm successfully hid a video in another cover video and both are of the same size; the hiding capacity was 100%. The algorithm achieved a SSIM that reached 0.97 and a high PSNR value that reached 68.8 proving that the imperceptibility of the proposed algorithm is very high. The comparative analysis shows that the suggested algorithm achieved higher imperceptibility than the other state-of-the-art algorithms regarding the average PSNR. The enhanced version of the proposed method was more robust against different types of attacks.

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Section: Introductionmentioning

confidence: 89%

“…The proposed algorithm achieved 100% embedding capacity which proves its higher efficiency. Embedding capacity is calculated as: [17].…”

Section: Embedding Capacitymentioning

confidence: 99%

High capacity video hiding based on multi-resolution stationary wavelet transform and hybrid-matrix decomposition techniqueset Transform and hybrid-matrix decomposition techniques

et al. 2022

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“…These methods often leverage the frequency coefficients to embed data imperceptibly. Examples include DST-based (Discrete Cosine Transform) methods [43]- [46], and DWT-based (Discrete Wavelet Transform) methods [47]- [56]. Frequency domain methods, although more complex than their spatial counterparts, have proven to be valuable tools for enhancing the concealment of data within video content.…”

Section: Literature Reviewmentioning

confidence: 99%

Hiding Data Within Thumbnail Videos: An Adaptive Downsampling-Resilient Video Steganography Method

Wang

2024

IEEE Access

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The rapid evolution of social media platforms presents novel opportunities and challenges for video steganography techniques. This paper focuses on taking thumbnail videos as the medium for data hiding, which are extensively utilized across social media platforms. The investigation into the method of embedding secret data into post-downsampled video leads to the proposal of an adaptive, downsampling-resistant method of video steganography, tailored to leverage the unique characteristics of these widely-used video formats. To obfuscate the detectability of the target frames, a pseudorandom number algorithm is employed that adaptively selects the target frames based on a secret key and the characteristics of the video itself. To mitigate the visual perturbations caused by data embedding, the luminance channel of the video serves as the embedding medium, and Syndrome-Trellis Codes (STC) are utilized to compute the embedding pixel positions before and after downsampling separately. Extensive evaluations of this method across various downsampling algorithms and scaling ratios were conducted. The experimental results demonstrate the method's effectiveness in ensuring that the hidden data remains undetectable and intact.INDEX TERMS Adaptive, hidden communication, steganography, thumbnail video.

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“…Rajesh and Shajin [98] utilized DCT coefficients of the frames in raw video streams to embed the secret information. The secret data embedding procedure includes the following steps; 1. extraction of the frame from the video stream, 2.…”

Section: Discrete Cosine Transformmentioning

confidence: 99%

Video steganography: recent advances and challenges

Kunhoth

Subramanian

Al‐Maadeed

et al. 2023

Multimed Tools Appl

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Video steganography approach enables hiding chunks of secret information inside video sequences. The features of video sequences including high capacity as well as complex structure make them more preferable for choosing as cover media over other media such as image, text, or audio. Video steganography is a prominent as well as the evolving field in the information security domain and significant number of video steganography methods are proposed in recent years. This article provides a comprehensive review of video steganography methods proposed in the literature. This article initially reviews various raw domain-based video steganography methods. In particular, the raw domain-based methods include spatial domain approaches such as least significant bits (LSB), transform domain-based methods such as discrete wavelet transform, discrete cosine transform, etc. Furthermore, the article looks into various compressed domain steganography methods. A critical comparative analysis is included in the article to analyze and contrast the steganography methods proposed in the literature. A brief description of various evaluation matrices for video steganography methods is provided in this article. Moreover, a brief introduction to steganalysis and video steganalysis is provided. The article concludes with a discussion focused on the limitations and challenges of the video steganography methods. Further, a brief insight into future directions in video steganography systems is provided.

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Steganography algorithm based on discrete cosine transform for data embedding into raw video streams

Cited by 7 publications

References 0 publications

High capacity video hiding based on multi-resolution stationary wavelet transform and hybrid-matrix decomposition techniqueset Transform and hybrid-matrix decomposition techniques

High capacity video hiding based on multi-resolution stationary wavelet transform and hybrid-matrix decomposition techniqueset Transform and hybrid-matrix decomposition techniques

Hiding Data Within Thumbnail Videos: An Adaptive Downsampling-Resilient Video Steganography Method

Video steganography: recent advances and challenges

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