Reversible Steganography Scheme Based on Position-Recording in DCT Coefficients

Lee, Wan-lung; Sun, Wei

doi:10.1109/cis.2019.00099

Cited by 6 publications

(2 citation statements)

References 10 publications

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“…The spatial domain algorithms embed secret by modifying the value of the image elements, such as Least Significant Bit (LS-B) based methods [14]- [16], Pixel Value Difference (PVD) based methods [17]- [19], and so on. The transform domain algorithms embed secret by modifying the transform domain coefficients, that are, Discrete Cosine Transform (DCT) [20], variants of Discrete Wavelet Transform (DWT) [21], and Fast Fourier Transform (FFT) [22]. Many state-of-the-art transform domain algorithms have emerged, such as Jsteg [23], OutGuess [24], StegHide [25], F5 [26], and so on.…”

Section: Related Workmentioning

confidence: 99%

Image Steganography Based on Artificial Immune in Mobile Edge Computing With Internet of Things

Ding

Xie

et al. 2020

IEEE Access

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Mobile edge computing provides high computing power, data storage capacity and bandwidth requirements for Internet of Things (IoT) through edge servers that process data close to data sources or users. In practical, mobile edge computing can be used to implement image steganography in IoT. Considering imperceptibility, security and capacity are important indicators for image steganography, this paper propose an image steganography based on evolutionary multi-objective optimization (EMOsteg). The EMOsteg preprocesses the image through a high-pass filters bank to find noise and texture regions that are difficult to model. By perturbing the image on noise and texture regions in multiple directions, the embedded capacity is increased. By defining the imperceptibility and security as an antigen, defining the perturbation positions of the cover image as an antibody, the EMOsteg uses the artificial immune principle to heuristically obtain the perturbation population through feature extraction of the perturbation and adaptive evolution operations. And the Pareto optimal is used to find the optimal perturbation in the last generation population. The simulation experiments analyze the convergence of the algorithm and the diversity of the solutions. In simulation experiments, the MSE, PSNR and SSIM were adopted to evaluate the imperceptibility, and the results show that the MSE value of our algorithm is 0.000308, the PSNR is 82.7501 and the SSIM approaches 1, they are better than comparison algorithms. The average detection error P E under SPA was adopted to detect the security, and the results show that our algorithm is more robust against anti-SPA steganalysis. In order to evaluate the performance of real-time, the embedding time of the same secret under different algorithms were compared, and the results show that our algorithm is faster than comparison algorithms in the terminal. In summary, the proposed algorithm can maintain the image quality while resist steganalysis tools, and realize real-time processing.

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Section: Related Workmentioning

confidence: 99%

Image Steganography Based on Artificial Immune in Mobile Edge Computing With Internet of Things

Ding

Xie

et al. 2020

IEEE Access

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“…Hence, video steganography has drawn more and more interest over the last few years. Generally speaking, there are four kinds of video steganography based on different positions: the intra-prediction mode [ 10 , 11 ], motion vector [ 12 , 13 ], Discrete Cosine Transform (DCT) coefficients [ 14 , 15 ] and entropy coding coefficient [ 16 ]. Because video steganography based on DCT coefficients and entropy coefficients considerably affect the video quality, only a few scholars focus on them.…”

Section: Introductionmentioning

confidence: 99%

A Secure Video Steganography Based on the Intra-Prediction Mode (IPM) for H264

Cao

Lan

2020

Sensors

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Recently, many video steganography algorithms based on the intra-prediction mode (IPM) have been adaptive steganography algorithms. These algorithms usually focus on the research about mapping rules and distortion functions while ignoring the fact that adaptive steganography may not be suitable for video steganography based on the intra-prediction mode; this is because the adaptive steganography algorithm must first calculate the loss of all cover before the first secret message is embedded. However, the modification of an IPM may change the pixel values of the current block and adjacent blocks, which will lead to the change of the loss of the following blocks. In order to avoid this problem, a new secure video steganography based on a novel embedding strategy is proposed in this paper. Video steganography is combined with video encoding. Firstly, the frame is encoded by an original encoder and all the relevant information is saved. The candidate block is found according to the relevant information and mapping rules. Then every qualified block is analyzed, and a one-bit message is embedded during intra-prediction encoding. At last, if the IPM of this block is changed, the values of the residual are modified in order to keep the optimality of the modified IPM. Experimental results indicate that our algorithm has good security performance and little impact on video quality.

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