Robust and hierarchical watermarking of encrypted images based on Compressive Sensing

Hong, Liu; Xiao, Di; Zhang, Rui; Zhang, Yushu; Bai, Song

doi:10.1016/j.image.2016.04.002

Cited by 46 publications

(23 citation statements)

References 32 publications

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“…These keys will be used for encryption and decryption process so these keys have to be kept secret from the intruders. Data transmitted over internet using copious dimensions are secretive and trust worthy [4]. Encryption is used to transmit the information accurately and securely.…”

Section: Introductionmentioning

confidence: 99%

An Improved Discrete Patch Based Reversible Data Hiding For Encoded Color Images

et al. 2020

IJEAT

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This paper proposes a system for encrypting images which is performed by patch wise separable reversible data. In the beginning, with the help of encryption key, a content writer prepares the unique uncompressed image. Then, the data-hider abridge encrypted images with least significant using data smacking key therefore to construct a sparse path that can incorporate with some additional data. The encrypted image data consisting of additional data, will aid the receiver to use only one encryption key to recall both additional data and image after decryption. The proposed system enables the receiver, to bring out the data and retrieving the actual content without an error by using both data-hiding key and encryption keys. The key generated is stored and the log is maintained. Data transmission through public communication system is unsecure due to be inaccuracy and improper exploitation by eavesdropper. The specific problem can be resolved by the technique Steganography, where the hidden messages are written in a way where it is only understood by the sender and intend recipient which gives the complete security for the messages. This proposed method includes Advanced Encryption Standard algorithm for encrypting both the image and the data. In order to achieve efficient working of encryption process, Separable Patch wise Reversible Data Hiding (SPRDH) algorithm is used in rescindable manner. The performance are analyzed using available Classical database images with the metrics Bits per Pixel (BPP). Peak Signal Noise Ratio (PSNR) and Mean Square Error (MSE).

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Section: Introductionmentioning

confidence: 99%

An Improved Discrete Patch Based Reversible Data Hiding For Encoded Color Images

et al. 2020

IJEAT

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“…In the meantime, considering the convenience and security of data storage and transmission, the compressive sensing (CS) theory is simultaneously introduced to image cryptosystem [42]- [47]. There are two types of measurements matrices that can be used in compressive sensing.…”

Section: Introductionmentioning

confidence: 99%

A robust image encryption algorithm based on Chua's circuit and compressive sensing

et al. 2019

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In terms of Chua's circuit system, compressive sensing (CS) and Haar wavelet, a novel image compression-encryption scheme (CES) is proposed in this paper. Firstly, the plaintext image is decomposed into approximate component and detail components through Haar wavelet. Then the approximate component is diffused by the threshold processing of local binary patterns (LBP) operator-based chaotic sequence which is produced by the combination of Chua's circuit and Logistic map. Next, the Lissajous map is applied to generate the chaos-combined asymptotic deterministic random measurement matrices (CADRMM) which are employed to measure the detail components in different compression ratios. In addition, the combination of mapped approximate and detail components is shuffled by the Logistic map. The experimental results and simulation analysis prove that the proposed cryptosystem is capable of reducing data for transmission and has good security performance under various attacks, especially for the shear and noise attacks.

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“…Furthermore, certain methods of CS can be implemented on existing devices with no hardware changes required [2]. CS reconstruction is also inherently immune to data loss [3] and the transferred data are naturally encrypted [4]. Since its introduction, CS was tested with WSNs performing temperature [5], EM emission [6], and ECG [7] monitoring, video streaming [8], etc.…”

Section: Introductionmentioning

confidence: 99%

Sparse Signal Acquisition via Compressed Sensing and Principal Component Analysis

Andráš

Dolinský

Michaeli

et al. 2018

Measurement Science Review

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This paper presents a way of acquiring a sparse signal by taking only a limited number of samples; sampling and compression are performed in one step by the analog to information conversion. The signal is recovered with minimal information loss from the reduced data record via compressed sensing reconstruction. Several methods of analog to information conversion are described with focus on numerical complexity and implementation in existing embedded devices. Two novel analog to information conversion methods are proposed, distinctive by their computational simplicity - direct subsampling and subsampling with integration. Proposed sensing methods are intended for and evaluated with real water parameter signals measured by a wireless sensor network. Compressed sensing proves to reduce the data transfer rate by >80 % with very little signal processing performed at the sensing side and no appreciable distortion of the reconstructed signal.

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Robust and hierarchical watermarking of encrypted images based on Compressive Sensing

Cited by 46 publications

References 32 publications

An Improved Discrete Patch Based Reversible Data Hiding For Encoded Color Images

An Improved Discrete Patch Based Reversible Data Hiding For Encoded Color Images

A robust image encryption algorithm based on Chua's circuit and compressive sensing

Sparse Signal Acquisition via Compressed Sensing and Principal Component Analysis

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