Propose Image Encryption Watermarking Algorithm Based on Frequency and Geometric Transform

WITHDRAWN: Contrasting the performance metrics of discrete transformations on digital image steganography using artificial intelligence

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.

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

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.

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.

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.

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 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).

To establish the secure communication using image steganography by hiding the information in cover image, the study focus on image steganography based on Ant Colony Optimization (ACO) where the cover image is divided into number of 5×5 blocks. As pixel values after ACO are considered as the optimal pixels, the ants search the next qualified pixels on reference to pheromone trails to encode the text messages. After ACO, Triangular Chaotic Map (TCM) is imposed based on initial value of chaotic sequences. The proposed method outperformed other state-of-art methods like classical Least Significant Bit(LSB), LSB with ACO, LSB with logistic map for all the images under consideration: lenna.png (0.00046, 83.4021, 0.0007, 0.9990964, 0.9983), baboon.png (0.00027, 82.5526, 0.0009, 0.9990542, 0.9985), pepper.png (0.00067, 71.2322, 0.0004, 0.9990560, 0.9947), dog.png (0.00045, 70.4590, 0.0005, 0.9990024, 0.9904) and flower.png (0.00067, 71.2322, 0.0004, 0.9990560, 0.9947) under the evaluation metrics as Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Mean Absolute Error (MAE), F-Score and Structural Similarity Index Matrix (SSIM) respectively.

Addition of hash component in a message is always for verification of authentication of message without integrity. In order to retain integrity certain schemes such as Merkle–Damgard scheme or Rabin scheme based on the block cipher can be used. However, the block cipher schemes in messages do not get applicable on image which are encoding message in a visual format. Therefore, block cipher based schemes are not able to provide tamper localization in case of image authentication. Tamper detection is needed in case of images as it is not visualized without proper verification. Moreover, localization is not possible by hash verification making the authentication processes only detectable but not identifiable. The paper presents a generation process of three least significant bits of hash function. The image insertion is not visualized due to human eye limitation. The method proposed is able to embed a secret image (gray scale) inside a corner image. Experimental results show an improvement in peak signal-to-noise ratio (PSNR) values of the proposed technique over the other techniques available, such as hash-based LSB(2-3-3) image steganography in spatial domain. This paper proposes an image authentication process not only for robustness, security, and tamper detection but also successfully able to identify tamper by a process of tamper localization. The parameters compared include the classical mechanism along with newly introduced entropy measurement of images. A performance analysis is able to show the result claimed in the paper. The paper uses a least significant bit (LSB) based hash function, which is a blind technique as image-related information is never sent to receiver separately. In fact, the proposed approach is a clever design as the generated hash function will be embedded in the image itself. The proposed mechanism is able to offer good imperceptibility between original image and embedded image with hash bits. Even a minute tampering can be detected with proper localization; the localization of tampering is having its wide applicability in case of forensic evidence of malicious image morphing.

Nowadays, the development of technology which involves multimedia data is widely used to help better understanding in spreading information. Image is known as 2D signal which contain huge data especially a high resolution image. This paper shows the comparison of applying lossy and lossless compression on the image data. Image compression is necessary in reducing the size of image for storage or transmission purpose to support most of the application nowadays. The technique applied in this paper is the hybrid of Discrete Wavelet Transform (DWT) technique and Huffman coding technique which are classified as lossy and lossless compression, respectively. The performance of image compression are evaluated in terms of compression ratio, Mean Square Error (MSE), Power Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM) and computing time. Several types of evaluation can determine better technique to apply on specific type of application. The stand-alone of each DWT and Huffman technique are evaluated before applying hybrid of DWT and Huffman technique. After conducting a comprehensive observation, the hybrid technique can compress with ratio about 1:17 to 1:27 due to the support from DWT technique that apply filter concept. The MSE value is high with the average about 69 which contributes to low PSNR value with about 29 to 30 dB due to the relation of PSNR equation with MSE value. Besides, the SSIM value is 0.6 or about 40% far from the original image that affect the output image. Despite of that, the computing time is fast with about 3 to 4 seconds which has been improved from stand-alone Huffman technique. Therefore, hybrid compression is capable of supporting each other techniques in stand-alone technique.

Data hiding is a process that secretly embedding information inside a data source without changing its original quality. Two popular techniques are steganography and cryptography [1]. Steganography is the art and science of hiding information by embedding messages into another image, audio or video [2]. Cryptography use mathematics to encrypt and decrypt data and transform plaintext into cipher text [3]. This study is about securing message by implementing the combination of steganography using Least Significant Bit (LSB) technique and cryptography using Vigenere cipher [4]. The methodology use is cyclic waterfall model. This model is simple and easy to understand. The phases also do not overlap with each other. The testing involves the process of embedding plaintext and cipher text into cover image. The results from the testing are the Mean Squared Error (MSE) and Peak Signal Noise Ratio (PSNR) value of the stego-image. The lower the MSE value and the higher the PSNR value is better image quality.

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 day-to-day life, information plays a major role. The value of those information becomes higher. So, we need to protect the information from intruders who try to get the secret information. In protecting those information, data compression deals a lot. Compression techniques are of two types which includes lossy and lossless compression. Steganography is the process which is used to protect the information by encrypting the compressed image with secret data and then extract the secret data from the compressed image by decryption. This paper utilizes an reversible data hiding (RDH) algorithm to boost the efficiency of encryption and decryption of the cover image by implementing the steganographic technique. RDH helps to accomplish the reason for picture content security. The encrypted data has been embedded within the cover image using the least significant bit (LSB). The proposed model has been evaluated based on criteria like savings percentage (SP%), compression time (CT), compression ratio (CR), mean squared error (MSE), and peak signal-to-noise ratio (PSNR). In comparison to previous systems that use the RSA algorithm, this technique has improved performance and system methodology.

Digital watermarking technology is increasingly used to protect copyright and demonstrate ownership of digital multimedia (such as text, music, photos, and videos). In order to safeguard intellectual property rights and rules of ownership for multimedia, this project suggests a text watermark algorithm. The process of hiding little text or grayscale images is the main focus, though. The masking of a watermark text in a high-color or high-density area of the block picture has been proposed using an embedding technique based on an energy function and the Least Significant Bits (LSB) method. Even with various format types and picture sizes chosen to conceal and cover a changing message size, the quality results demonstrate that the watermark image suffers from less distortion than the cover image, and the suggested algorithm is powerful to conceal a random watermark text even with smaller block sizes. An additional optional choice to encrypt the text watermark before embedding is also recommended because doing so would make it harder for hackers to read the text. This text can be encrypted using the Caesar cipher method before embedding is implemented in images.The experimental results of using the suggested algorithm for embedding and extracting watermark text for various sizes in a large number of images were satisfactory, giving a level of peak signal-to-noise ratio (PSNR) and Signal to Noise Ratio (SNR) with low mean square error (MSE) values. However, PSNR degrades more quickly than LBS as the watermark text size increases, so it was determined that it is more suitable for applying a watermark rather than a stego It is employed in order to share information securely