Covariance Based Steganography Using DCT

WITHDRAWN: Contrasting the performance metrics of discrete transformations on digital image steganography using artificial intelligence

With the development of depth data acquisition technologies, access to high-precision depth with more than 8-b depths has become much easier and determining how to efficiently represent and compress high-precision depth is essential for practical depth storage and transmission systems. In this paper, we propose a layered high-precision depth compression framework based on an 8-b image/video encoder to achieve efficient compression with low complexity. Within this framework, considering the characteristics of the high-precision depth, a depth map is partitioned into two layers: 1) the most significant bits (MSBs) layer and 2) the least significant bits (LSBs) layer. The MSBs layer provides rough depth value distribution, while the LSBs layer records the details of the depth value variation. For the MSBs layer, an error-controllable pixel domain encoding scheme is proposed to exploit the data correlation of the general depth information with sharp edges and to guarantee the data format of LSBs layer is 8 b after taking the quantization error from MSBs layer. For the LSBs layer, standard 8-b image/video codec is leveraged to perform the compression. The experimental results demonstrate that the proposed coding scheme can achieve real-time depth compression with satisfactory reconstruction quality. Moreover, the compressed depth data generated from this scheme can achieve better performance in view synthesis and gesture recognition applications compared with the conventional coding schemes because of the error control algorithm.

A secure image steganography algorithm based on least significant bit and integer wavelet transform

A comparative analysis of image steganography based on DCT algorithm and steganography tool to hide nuclear reactors confidential information

There is a huge resource of data available on the internet which one can access without realizing that the person is even authorized to access it or not. The hard work of the original resource person can easily be compromised. Digital watermarking is an answer to overcome this issue. This paper introduces a hybrid of LSB and DCT techniques, LSB(Least Significant Bit) and DCT(Discrete Cosine Transformation). The paper studies the two techniques along with the proposed technique and a comparison is drawn between the three based on MSE and PSNR values obtained. The introduced hybrid technique performs better in comparison to DCT and LSB. The MSE calculated was 64% better than LSB and 60% better than DCT resultantly PSNR is also observed to be better than LSB and DCT.

Steganography is the practice of hiding data, such as images, videos, or text, within a cover image without it being detectable by the human eye. Several factors, such as the capacity, security, and robustness of the technique, are essential when transferring information using this method. In this study, we propose a new approach to image steganography that improves the Least Significant Bit (LSB) technique by utilizing images of 24 bits in each pixel. Improving the capacity and security of LSB-based steganography requires a combination of techniques, such as indirect embedding, embedding in multiple channels, and applying cryptographic and compression techniques. This approach conducts by encrypting each compressed secret message bit with the most significant bit of the red channel and then saving the output bit (hidden bit) in the least significant bit of the (green/blue) channel according to the row value (odd/ even). To further security, the suggested approach uses multi-level encryption; employs RSA to encrypt the secret message before applying the Huffman compression and encrypting the hidden bit by (XOR/XNOR) in the embedding method based on the row value of the pixel. Meanwhile, it is planned to use the Huffman coding technique to shorten the length of the encrypted message that will be inserted in the cover image. For the color photos in this work, the standard images were acquired from a standard dataset (USC-SIPI). The suggested approach performs better when measured in terms of mean square error (MSE), peak signal-to-noise ratio (PSNR), and comparison to findings from related prior efforts.

Effective self-embedding watermarking scheme for image tampered detection and localization with recovery capability

Aim: This paper mainly focused on introducing a new framework for image and text hiding using a simple Least Significant Bit (LSB) substitution method.  Results: Six 24-bit images are used as reference images. XOR operation is used in the stego key to generate new bit planes of the stego images. An RGB color image is used as a secret cover image. The proposed method dramatically increases the embedding capacity without significantly decreasing the Peak Signal-to-Noise Ratio (PSNR) value.  Conclusion: This method increased the compression ratio, embedding ratio, PSNR and Space 24%, 53%, 36% and 47%, respectively. The result shows that the newly developed method improved the value of accuracy by 30% and sensitivity by 16% for the hidden images.  Keywords: LSB, PSNR, FNR (False Negative Rate), Sensitivity, MSE (Mean Square Error), Specificity HIGHLIGHTS: The newly developed method with simple Least Significant Bit (LSB) improved the accuracy value by 30%, and sensitivity by 16% for the hidden image. The improved LSB method increased security and preserved the quality of hidden images.

In spatial domain image steganography, Least Significant Bits (LSB) of cover image pixels are used to embed a secret message due to minimal distortion and higher payload capacity. In this paper, we have introduced an exclusive-OR (XOR) based encoding of encrypted secret message bits using varying higher-order pixel intensity bits. Encoding and LSB embedding is done block-wise by dividing the cover image into a number of blocks. The secret message is first encrypted using symmetric key cryptography and then encoded those encrypted bits by XORing them with randomly selected higher-order pixel bis of the cover image to obscure the secret bits further. Next, an inversion technique is applied to the encoded bits block-wise to keep the LSB bit changes to a minimum. The stego-key consists of the symmetric encryption key and the encode-key containing parameter settings such as the number_of_blocks, starting_block, start_pixel_offset, block_selection_rule, etc. This stego-key is shared prior to the actual communication using public-key cryptography to ensure the key’s authenticity and integrity. The extraction process does not require the cover image; the stego-image and the stego-key are sufficient. Experimental results show the visual imperceptibility along with improved image quality metrics such as Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Normalized Cross-Correlation (NCC), and Structural Similarity (SSIM) index in comparison to other well-known techniques. The average PSNR value remains above 51dB, even with 90% of the capacity utilized. The proposed scheme successfully eludes many standard steganalysis attacks such as histogram-based analysis (PDH), chi-square based embed probability test, Regular and Singular groups (RS) analysis, sample pair test, etc. on the tested stego-images.

Presently, multi-day data security is the greatest issue of challenging over the world. There are various systems accessible for image and data security; watermarking is one of them. This paper proposes a new technique for watermarking encryption image by using LSB and based on the frequency and geometric transform. In this work, the Discrete Wavelet Transform (DWT) technique is used to deal with the cover image at the frequency domain without spatial domain where late studies have shown the strength of this type of transform. The rotation geometric transforms applying on the logo image to preserve it and to protect it from eavesdropping and unauthorized entities. The rotate transform considers the type of disguise. Therefore, to increase the security of the watermarking system, it should be considered to also apply Rivest Cipher 4 (RC4) encryption algorithms on logo image before perform watermarking embedding. In finally Least Significant Bit (LSB) is used to embed a logo image in the cover image. The demonstrated experiment is based on Peak Signal to Noise Ratio (PSNR) and Mean Squared Error (MSE), the DWT achieves better results as compared to other methods when the rate of PSNR reached from 50 dB to 60 dB.

This paper presents hiding one to eight gray images or texts (secret information) inside color image (cover image) based on Least Significant Bits (LSB) algorithm. The main idea is to insert the secret message (one to eight texts or one to eight gray images) in the three LSB of the cover image (color image). The color cover image RGB model (R channel, G channel and B channel) is separated into three cover images (the red cover, green cover, and blue cover). Each one of these three cover images is used to hide secret messages (gray image (two secret images in R channel, three secret images in G channel and three secret images in B channel) or text). The experiments and comparative studies show that the algorithms are characterized by many features of the ability of hiding huge data, and then the ability of extracting secret message without errors. Beside the reconstructed image, has efficacies (to human acquaintance) according to peak signal to noise ratio (PSNR) and mean square error (MSE), also retain both the explicitness and the characteristics of the both secret message and cover image.

We have designed, fabricated and successfully tested digital error-correction circuits to improve the performance of superconductive flash analog-to-digital converters (ADCs). The comparators coding the most significant bits (MSBs) are the least sensitive to the input signal, and therefore have the most threshold errors due to jitter and threshold misplacement. These errors are completely eliminated by implementing an ADC architecture using two comparators per bit, and employing logic to encode bit N by looking back to the state of the (N-1) bit. In this way, all code transitions are derived from the least significant bit (LSB) comparators. The MSB comparators are used only to encode the LSB data.

The goal of image steganographic methods considers three main key issues: high embedding capacity, good visual symmetry/quality, and security. In this paper, a hybrid data hiding method combining the right-most digit replacement (RMDR) with an adaptive least significant bit (ALSB) is proposed to provide not only high embedding capacity but also maintain a good visual symmetry. The cover-image is divided into lower texture (symmetry patterns) and higher texture (asymmetry patterns) areas and these textures determine the selection of RMDR and ALSB methods, respectively, according to pixel symmetry. This paper has three major contributions. First, the proposed hybrid method enhanced the embedding capacity due to efficient ALSB utilization in the higher texture areas of cover images. Second, the proposed hybrid method maintains the high visual quality because RMDR has the closest selection process to generate the symmetry between stego and cover pixels. Finally, the proposed hybrid method is secure against statistical regular or singular (RS) steganalysis and pixel difference histogram steganalysis because RMDR is capable of evading the risk of RS detection attacks due to pixel digits replacement instead of bits. Extensive experimental tests (over 1500+ cover images) are conducted with recent least significant bit (LSB)-based hybrid methods and it is demonstrated that the proposed hybrid method has a high embedding capacity (800,019 bits) while maintaining good visual symmetry (39.00% peak signal-to-noise ratio (PSNR)).

In recent years, internet revolution resulted in an explosive growth in multimedia applications. The rapid advancement of internet has made it easier to send the data/image accurate and faster to the destination. Besides this, it is easier to modify and misuse the valuable information through hacking at the same time. Digital watermarking is one of the proposed solutions for copyright protection of multimedia data. A watermark is a form, image or text that is impressed onto paper, which provides evidence of its authenticity. In this paper an invisible watermarking technique (least significant bit) and a visible watermarking technique is implemented. This paper presents the general overview of image watermarking and different security issues. Various attacks are also performed on watermarked images and their impact on quality of images is also studied. In this paper, Image Watermarking using Least Significant Bit (LSB) algorithm has been used for embedding the message/logo into the image. This work has been implemented through MATLAB. Keywords - Watermarking, Least Significant Bit (LSB), JPEG (Joint Photographic Experts Group), Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR).

Background and Objective: The public and group communication carried out in the social, cloud, and mobile networks suffer from unauthorized users. The data security is required for secure authentication, monetary transactions and other sensitive information. The steganography methods empower the user with invulnerable communication in public domain. In this paper, a region secure and pattern based alternate 2B-3C (2Bit-3Channel) Steganography method is proposed to improve the content reliability and data security. Methods: In this method, the cover pixels are retrieved by applying the spiral rectangular pattern over the cover image. This spiral pattern also secures the core content region and the pixels from the core ROI (Region of Interest) is used as a cover only for larger size secret information. In this proposed steganography method, two channels are considered alternatively based on the defined rules. The LSB (Least Significant Bit) of both channels is XOR with input data bits and key to perform data hiding. The method is applied on real time color images taken from COREL and USC-SIPI-ID. The evaluation of proposed steganography approach is done using MSE (Mean Square Error), PSNR (Peak Signal-to-Noise Ratio), BER (Bit Error Rate), NCC (Normalized Cross Correlation) and SSIM (Structural Similarity Index Matrix). Result: The comparative results are generated for 50 real time images against the existing LSB (Least Significant Bit), LSBM (Least Significant Bit Modulation), LSBMR (Least Significant bit Matched Revisited), SCC (Stego Color Cycle), SHSI (Simple Hue-Saturation-Intensity), HIS-MLSB(Simple Hue-Saturation-Intensity-Modified LSB) and IMMEA(Iterative Magic Matrix Encryption Algorithm) methods. Conclusion: The experimentation results verified that the proposed 2B-3C approach improved the data hiding in qualitative and quantitative aspects.