Separable data hiding in encrypted image based on compressive sensing and discrete fourier transform

Liao, Xin; Li, Kaide; Yin, Jiaojiao

doi:10.1007/s11042-016-3971-4

Cited by 176 publications

(57 citation statements)

References 20 publications

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“…The workflow of data extraction and recovery stage is explained in Figure 4. (6) where, MSE is the Mean Square Error which is used to measure the error between the original image and compressed image and is computed using (7).…”

Section: Rbmentioning

confidence: 99%

“…Reversible data hiding technique is used in some special applications such as Military images, Medical Images and Forensics, where the exact recovery of the original cover image is inevitable. Data hiding techniques can be carried out in three domains [2] namely; Spatial Domain [3,4], Frequency Domain [5,6,7], and Compression Domain [8,9,10]. In the Spatial Domain based data hiding techniques, the secret data is embedded by modifying the pixel values directly.…”

Section: Introductionmentioning

confidence: 99%

“…Then we extract the embedded secret data from Stego Image thereby leading to original Cover Image. The Peak Signal to Noise Ratio (PSNR) is used to measure the quality of the compressed image using(6).…”

mentioning

confidence: 99%

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Reversible Data Hiding Technique using AMBTC based Bitmap Manipulation

Uma¹,

Vimala²

2020

IJCA

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In this research work, it has been proposed to use images to hide the secret data as it is difficult to extract secret data from the image. Using images to hide and transmit secret data, leads to additional overhead of increased cost associated with storage and transmission cost, as the image requires more space for storage. However, hiding data inevitably destroys the host image, even though the distortion is imperceptible. To overcome such drawbacks, image compression techniques are used for both, hiding the secret data and to reduce the storage and transmission cost. To enhance the hiding capacity and maintain the quality of the host image after embedding hidden data, we present a high payload reversible data hiding scheme that is based on the Absolute Moment Block Truncation Coding (AMBTC) compression domain. We exploit the feature of inter block redundancy in an AMBTC compressed image to improve the coding efficiency of compressed images. Normally, the AMBTC technique transforms an input image into a set of blocks and each block in turn is transformed into a set of a bit-plane and two quantizers. But in the proposed method, these blocks are categorized into Shade and Edge blocks based on the magnitude of amplitude values. For a Shade block, two values are stored, one being the block mean and the other value being the secret data. Two bytes of secret data is stored creating an illusion that the bitplane is stored. For Edge blocks, high mean and low mean are stored as two quantizers and a respective Bitplane is generated. The shade block helps in embedding 3 bytes of secret data leading to higher embedding capacity and increases the complexity of identifying the existence of secret data. It also compresses the stego-image without much degradation in the visibility of stego image.

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Section: Rbmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Reversible Data Hiding Technique using AMBTC based Bitmap Manipulation

Uma¹,

Vimala²

2020

IJCA

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“…(A) Data protection in terms of CS has been discussed in [136]- [141]. Fakhr in [137] proposed a watermark embedding and recovery technique based on the CS framework, tested under MP3 compression.…”

Section: Cs In Watermarkingmentioning

confidence: 99%

On some common compressive sensing recovery algorithms and applications

Draganic

Orović

Stanković

2017

Facta Univ Electron Energ

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Compressive Sensing, as an emerging technique in signal processing is reviewed in this paper together with its' common applications. As an alternative to the traditional signal sampling, Compressive Sensing allows a new acquisition strategy with significantly reduced number of samples needed for accurate signal reconstruction. The basic ideas and motivation behind this approach are provided in the theoretical part of the paper. The commonly used algorithms for missing data reconstruction are presented. The Compressive Sensing applications have gained significant attention leading to an intensive growth of signal processing possibilities. Hence, some of the existing practical applications assuming different types of signals in real-world scenarios are described and analyzed as well.

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“…Xiao and Chen [10] left some space in the image for embedding data later to achieve separability. The quality of the decrypted image is improved by Liao et al [11] using compressive sensing and discrete Fourier transform (DFT). Qian and Zhang [12] compressed some bits from the encrypted image to find room for hiding.…”

Section: Introductionmentioning

confidence: 99%

Separable Reversible Data Hiding in Encrypted Signals with Public Key Cryptography

Tai

Chang

2018

Symmetry

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Abstract:We propose separable reversible data hiding in an encrypted signal with public key cryptography. In our separable framework, the image owner encrypts the original image by using a public key. On receipt of the encrypted signal, the data-hider embeds data in it by using a data-hiding key. The image decryption and data extraction are independent and separable at the receiver side. Even though the receiver, who has only the data-hiding key, does not learn about the decrypted content, he can extract data from the received marked encrypted signal. However, the receiver who has only the private key cannot extract the embedded data, but he can directly decrypt the received marked encrypted signal to obtain the original image without any error. Compared with other schemes using a cipher stream to encrypt the image, the proposed scheme is more appropriate for cloud services without degrading the security level.

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Separable data hiding in encrypted image based on compressive sensing and discrete fourier transform

Cited by 176 publications

References 20 publications

Reversible Data Hiding Technique using AMBTC based Bitmap Manipulation

Reversible Data Hiding Technique using AMBTC based Bitmap Manipulation

On some common compressive sensing recovery algorithms and applications

Separable Reversible Data Hiding in Encrypted Signals with Public Key Cryptography

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