A Novel Separable Scheme for Encryption and Reversible Data Hiding

Chen, Pei; Lei, Yang; Niu, Ke; Yang, Xiaoyuan

doi:10.3390/electronics11213505

Cited by 5 publications

(3 citation statements)

References 33 publications

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“…In the study [42], the authors introduced the addition and removal of content and images as a form of tampering on some regions in the encrypted video and also performed a recovery of these regions using the POB number system. Another study [43] investigated whether hidden data could be retrieved from encrypted videos by using noise as a sketch attack. By using an enhanced encrypted watermarking technique, the authors [44]detect video tampering using a watermarked blockchain.…”

Section: Tampering and Its Detection In Encrypted Visual Contentmentioning

confidence: 99%

Pixel Tampering Detection in Encrypted Surveillance Videos on Resource-Constrained Devices

Aribilola,

Lee,

Asghar

2024

Preprint

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Encryption (naïve/selective) is recommended to secure the recorded visual content; however, intruders can still manipulate encrypted data. Visually, tampering attacks on encrypted video pixels in selectively encrypted videos are difficult to identify. Thus, this paper presents a tampering detection system that performs vulnerability analysis for Regions-of-Interest (ROI) in encrypted videos. To detect the tampering attacks, we explored the pixels' intensities and proposed a new TampDetect algorithm. The TampDetect applies the Hue, Saturation, and Value (HSV) colour model to detect the encrypted areas in the video. These encrypted pixels are then segmented and selected from the non-encrypted pixels using a minimum and maximum HSV value and a global threshold. The mean intensity of the encrypted pixels is thus calculated and stored. The integrity of the video frame is then validated by comparing the stored mean intensity with the newly calculated mean intensity to validate tampering/attack. The experiments were conducted on an Intel NUC, and its low computational cost demonstrates the lightweight nature of the proposed TampDetect algorithm for detecting tampering in ROI encrypted videos. The developed dataset for experiments, i.e., original, ROI encrypted, and tampered videos (encrypted/decrypted) is made available on kaggle-repository for future researchers.

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Section: Tampering and Its Detection In Encrypted Visual Contentmentioning

confidence: 99%

Pixel Tampering Detection in Encrypted Surveillance Videos on Resource-Constrained Devices

Aribilola,

Lee,

Asghar

2024

Preprint

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show abstract

“…This scheme combines the idea of two-layer embedding to further increase the embedding capacity. Chen et al [25] proposed a novel separable scheme for encryption and reversible data hiding. The embedding algorithm used in the proposed scheme can provide a higher capacity in the video with a lower quantization parameter and a good visual quality of the labeled decrypted video, maintaining low bit rate variation.…”

Section: Related Workmentioning

confidence: 99%

High-Embedded Low-Distortion Multihistogram Shift Video Reversible Data Hiding Based on DCT Coefficient

et al. 2023

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Video reversible data hiding technology can be applied to copyright protection, medical images, the military, and other fields, but it cannot guarantee high visual quality with an effective embedded capacity. In this paper, a high-embedding and low-distortion reversible data hiding scheme based on a discrete cosine transform (DCT) coefficients method is proposed. The scheme first decodes the original video stream with entropy, obtains all the DCT blocks, and selects the embeddable DCT blocks according to the capacity of the zero factor. Then, it divides the coefficients in the DCT blocks into the shift and embedding coefficients. The shift coefficients directly generate a one-dimensional histogram; the embedding coefficients generate a two-dimensional histogram according to paired strategies. Finally, the secret data can be successfully embedded according to the proposed two-dimensional histogram shift reversible data hiding scheme. This scheme performed more effectively than existing schemes in terms of the embedded capacity, peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM).

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“…In this case, we can directly extract the watermark information from the distorted image I a for copyright verification. We adopted a generic reversible algorithm framework and traditional reversible watermarking methods such as histogram modification (HM) [24], pixel value ordering (PVO) [25], difference expansion (DE) [26], and prediction error expansion (PEE) [27] techniques. In this paper, we specifically used difference expansion.…”

Section: Integrity Informationmentioning

confidence: 99%

Two-Stage Robust Lossless DWI Watermarking Based on Transformer Networks in the Wavelet Domain

Liu

Zheng

et al. 2023

Applied Sciences

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For copyright protection of diffusion-weighted imaging (DWI) images, traditional robust watermarking techniques result in irreversible distortions, while reversible watermarking methods exhibit poor robustness. We propose a two-stage lossless watermarking algorithm based on a Transformer network to solve this problem. The first stage of the algorithm is to train the robust watermarking network, embed the watermark into the cover image in the wavelet domain, and design the frequency information enhancement module to improve the reconstruction quality. In the second stage, based on the pre-trained robust watermarking network, the difference image between the watermarked image and the cover image is reversibly embedded into the watermarked image as the compensation information to losslessly recover the cover image. The difference image is compressed using DCT and Huffman coding to reduce the compensation information. Finally, the watermark extraction network is trained on the second embedding result to avoid weakening the robustness of the first stage caused by the reversible embedding. The experimental results demonstrate that the PSNR of the watermarked image reaches 60.18 dB. Under various types of image attacks, the watermark extraction BER is below 0.003, indicating excellent robustness. The cover image can be recovered losslessly under no attack.

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A Novel Separable Scheme for Encryption and Reversible Data Hiding

Cited by 5 publications

References 33 publications

Pixel Tampering Detection in Encrypted Surveillance Videos on Resource-Constrained Devices

Pixel Tampering Detection in Encrypted Surveillance Videos on Resource-Constrained Devices

High-Embedded Low-Distortion Multihistogram Shift Video Reversible Data Hiding Based on DCT Coefficient

Two-Stage Robust Lossless DWI Watermarking Based on Transformer Networks in the Wavelet Domain

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