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LSB matching revisited is an LSB-based approach for image steganography. This method is a type of coding to increase the capacity of steganography. In this method, two bits of the secret message are hidden in two pixels with only one change. But this method provides no idea for hiding a message with a large number of bits. In other words, this meth...
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Citations
... However, the space-efficient nature of conveying meta-data (PLS) and the need to balance security and space efficiency pose limitations in this context. The authors in [21] improve the LSB with matching revisited technique by efficiently hiding messages with more than two bits while minimizing alterations to the image. However, this method could lead to increased computational demands due to the complexity of the operations required for embedding and retrieving messages. ...
This paper addresses the scientific problem of enhancing the security and capacity of steganographic methods for protecting digital media. The primary aim is to develop an advanced steganographic technique that optimizes quantization tables to surpass the traditional F5 algorithm in terms of security, capacity, and robustness. The novelty of this research lies in the introduction of the F5A method, which utilizes optimized quantization tables to significantly increase the capacity for concealed information while ensuring high-quality image retention and resistance to unauthorized content recovery. The F5A method integrates cryptographic keys and features to detect and prevent copyright infringement in real time. Experimental evaluations demonstrate that the F5A method improves the mean square error and peak signal-to-noise ratio indices by 1.716 and 1.121 times, respectively, compared to the traditional F5 algorithm. Additionally, it increases the steganographic capacity by up to 1.693 times for smaller images and 1.539 times for larger images. These results underscore the effectiveness of the F5A method in enhancing digital media security and copyright protection.
... The method for using LSB substitution to hide secret data inside digital photos was used for securing the messages [10,11]. The authors provide a method that can include sensitive information into the LSBs of pixel values without materially changing the look of the cover image. ...
The new data hiding method that is suggested in this study is based on the variations in picture interpolation methods. To conceal data in a cover picture, our method takes use of variations in interpolation methods. We specifically create two intermediate pictures using the bicubic and nearest-neighbor interpolation techniques, and then embed the data in the difference between these images. According to the findings of our experiments, our approach successfully achieves high embedding capacity and good invisibility. Our method is also resistant to a variety of picture editing techniques, such as rotation, scaling, cropping, and JPEG compression.
... In the spatial domain, the hidden message is concealed directly into the pixels of a cover image. The most commonly used technique is the Least significant bit (LSB) including its variants [10,20,26]. In the frequency domain, the hidden message is concealed in the image's discrete cosine transform (DCT) domain. ...
... A number of encryption methods have been proposed Text -LSB and new edge detection method to increase the payload capacity at the edge area of the cover image -Maintain stego image quality with increased capacity compared to the prior work [37] 2020 Text -LSB and Huffman coding -Low capacity [41] 2020 Text -Filtering-based and modified LSB -Low capacity [17] 2020 Secret data bits (SDB) -LSB, Image Region Decomposition (IRD) and the dynamic number of LSB for hiding patient info into MRI Image -Highly imperceptible and indistinguishable to the human eye. However, the largest size of secrete image is only 130 KB for a 1024 × 1024 cover image [38] 2021 Single channel image -Modified LSB and a medical image is encrypted using one-dimensional piecewise chaotic map -Every bit of the secret image is transmitted without any loss [20] 2021 Text -Modified LSB to conceal medical info without leaving a detectable forgery in the stego image -Capacity is not mentioned [26] 2021 Single channel image -Modified LSB and converting the secret message into a bit-stream and divided into a set of blocks including n bits in each block -Higher capacity than the F5 method but the hidden image is too small [10] 2023 Image -Proposed a Huffman code LSB based image steganography technique using multi-level encryption and achromatic component of an image -Easy to program, simple, but low embedded capacity [33] DCT Based Year Secrete info ...
Several medical consultations and examinations have been undertaken online since the Covid outbreak. However, when private data was communicated over the internet or uploaded to the cloud, medical information became more susceptible to security risks. Steganography is a technique that can be used to hide sensitive information within a cover image. This paper presents four improved algorithms to enhance steganography's performance in medical images. A full-size hidden image that is as huge as a cover image cannot be handled by previous methods, which is what the algorithmic design is meant to address. Several creative methods are presented, including the computation of Discrete Cosine Transform (DCT) coefficients based on scaled floating values, the addition of an adaptive compression matrix, and a new approach for systematically dispersing a concealed number of bits across multiple separate locations in the cover image. The results of the experiment showed a notable advancement over the earlier research. Our secret image size is substantially larger than the past studies, yet the structure similarity index matrix (SSIM) of the best reconstructed secret image is close to ideal, the peak signal-to-noise ratio (PSNR) and the payload capacity are higher than in the previous studies. This research is beneficial since it contributes to a medical application for enhancing the security of information concealed in chest X-ray images. Medical personnel can generate an image that conceals patient information in a secure manner.
... The earlier approaches to steganography primarily relied on LSB (Least Significant Bit) substitution [18][19][20][21][22], where secret data is directly embedded into specific regions of the image by replacing the least significant bits. This method was popular due to its simplicity and minimal impact on the visual appearance of the cover image. ...
... Fateh et al. [18] proposed a coding scheme to improve steganography capacity with the LSB revisiting approach. The secret message is divided into several blocks with a different n number of bits. ...
In today’s rapidly evolving landscape of communication technologies, ensuring the secure delivery of sensitive data has become an essential priority. To overcome these difficulties, different steganography and data encryption methods have been proposed by researchers to secure communications. Most of the proposed steganography techniques achieve higher embedding capacities without compromising visual imperceptibility using LSB substitution. In this work, we have an approach that utilizes a combination of Most Significant Bit (MSB) matching and Least Significant Bit (LSB) substitution. The proposed algorithm divides confidential messages into pairs of bits and connects them with the MSBs of individual pixels using pair matching, enabling the storage of 6 bits in one pixel by modifying a maximum of three bits. The proposed technique is evaluated using embedding capacity and Peak Signal-to-Noise Ratio (PSNR) score, we compared our work with the Zakariya scheme the results showed a significant increase in data concealment capacity. The achieved results of our work show that our algorithm demonstrates an improvement in hiding capacity from 11% to 22% for different data samples while maintaining a minimum Peak Signal-to-Noise Ratio (PSNR) of 37 dB. These findings highlight the effectiveness and trustworthiness of the proposed algorithm in securing the communication process and maintaining visual integrity.
... Elapsed time, MSE, PSNR, and Compression ratio were the metrics used and the system does not work on different types of datasets of images or other types of digital media, [8]. The study, [9], solved Information hiding capacity in steganography using Novel LSB with the strength of Using coding to increase steganographic capacity method and weakness of no idea for hiding messages with a large number of bits, MSE, PSNR, capacity, and SSIM are used for evaluation. The study, [10], addressed the problem of data and information hiding in digital images using the Bitmap Steganography technique under the implementation called Any file can be hidden in an image, can take any type of image file without converting it to bitmap and using maximum memory space to hide files in pictures. ...
The Security of confidential communication is protected using the most popular type of carrier to hold information known as Image steganography. The Least Significant Bit (LSB) algorithm and the Most Significant Bit (MSB) algorithm are steganography algorithms used for information hiding in digital images both have disadvantages of Low image quality, Security, vulnerability to any small modifications, and long encoding time during message compression. To overcome this limitation, the research proposes a Secured Hybrid algorithm called S-Hybrid to combine (LSB and MSB) bits based on checking Two bits (the least significant bit and the most significant bit) of the cover images and replace them with a secret message which was implemented in Netbeans IDE. However, the S-Hybrid algorithm produced the best stego-image quality. Large cover images made the hybrid algorithm’s quality better. The proposed S-Hybrid had a lesser encoding time than the existing method having the highest compression ratio which reduces the transmission effort making the encoding time short which is correlated to the security and makes the proposed method perform better than the existing one. Therefore, a trade-off exists between the encoding time and the quality of stego-image as demonstrated in this work. Mean-squared error (MSE), Peak signal-to-noise ratio (PSNR), encoding time, and Compression ratio are used for performance evaluation between the proposed S-Hybrid algorithm and the existing Method after embedding messages in digital images.
... Ants optimize their search by identifying the best solutions and taking into account earlier markings. The embedding procedure in this work will be based on the best path in graph number three, as indicated in the figure (3). ...
... The results of objective tests are listed in table (3). This table contains the values of the objective tests applied to the stego-image and cover image. ...
Steganography, which is the science of delivering a message between parties in a way that an eavesdropper will not be aware that the message exists, is one of the key disciplines that have a considerable interest in fields. The suggested method seeks to conceal a smaller color image within a larger color image. It utilizes the transform domain throughout the steganography process to increase its resistance to changes and treatments made to the cover image. In order to achieve both complexity security and robustness, the project seeks to implement and utilize two techniques: ant colony optimization and transformation domain approach. The technologies under consideration suggest a Steganography method for digital photographs. It employs Discrete Cosine Transform (DCT) to achieve the same aims in terms of security, transparency and robustness. Additionally, it makes use of Once an Ant Colony Optimization (ACO) to increase robustness against signal processing attacks and imperceptibility in accordance with the human visual system. This work implements ACO for the cover to find the embedding locations on the graph path, and then finds locations to hide information based on threshold method, when looking for places to hide information blocks, DCT uses an intelligent block matching technique between the embedded image and the cover image, and both systems were tested against each other to compare their performance. Six stages make up the proposed secret key steganography system: test, transform, key creation and substitution, ant colony optimization, matching, inverse transform, and key encryption and concealing.
... In recent years, most of the video steganography work has been implemented using the least significant bit (LSB) as seen in [6,26,27]. From simple LSB to advanced hybrid version of the LSB, the method can be applied in various steganographic schemes, can be noted down in [1,12,33], which claims high payload but robustness to steganalysis methods is rarely maintained. Some spatial domain techniques implemented in video steganographic schemes are matrix encoding, region of interest (ROI), bit-plane complexity segmentation (BPCS), mapping rules, etc. ...
Information security holds a quintessential role in the era of digital communication. Nowadays, social media has become the new platform to share a massive length of digitally transmitted multimedia files without being suspected. Hence, it can hide data, enabling the security providers to add an extra layer to the existing traditional framework. Videos are the most shared digital content and carry the maximum payload, which is best suitable for steganography. This paper suggests a secured stego key-based video steganographic method that uses Framelet Transform to embed secret data in the cover media. Here the main focus is to reduce the computational cost by introducing the stego key, which reserves the information regarding the location of the secret data. For an additional layer of security, the stego key is encrypted using Elliptic Curve Cryptography (ECC) based encryption scheme. The robustness of the scheme is enhanced by introducing a large prime number for the stego key sharing using the Elliptic Curve Diffie Hellman Key Exchange Protocol. Performance measures, including PSNR, MSE, SSIM, and BER, are compared with the traditional state-of-the-art methods, which produce significant results without tampering with the visual quality and perceptual characteristics of the stego video.
... Image steganography methods that embed secret data into particular ROIs within an image are relatively new approaches. Edge regions are one of the ideal image ROIs for data concealment because the human visual system is less sensitive to distortions in edge regions, and it also provides randomized pixel placements [8,9]. ...
... trace(M) is the sum of diagonal elements of matrix M. It can be computed using equation (9). ...
Internet technology has revolutionized the landscape of communication technologies in the modern era. However, because the internet is open to the public, communication security cannot be guaranteed. As a result, data concealment approaches have been developed to ensure confidential information sharing. Various methods have emerged to achieve the goal of secure data communication via multimedia documents. This study proposes a method, which is both adaptable and imperceptible, for concealing a secret text in a color image. From an adaptivity perspective, image corners are detected using the Harris corner detection algorithm and utilized as anchor points for picking the optimal hiding regions of interest using Bezier curve interpolation. On the other hand, because human vision is less sensitive to aberrations in edge regions, imperceptibility is guaranteed by utilizing curves that cross through these regions. Experiments indicate that utilizing gradient selective Bezier curves for secret text concealment can keep the imperceptibility even when the payload capacity is increased.
... Это связано с тем, что растровые изображения, аудиофайлы и видеофайлы содержат большие объемы малозначимой информации. Наиболее развитый метод замены наименее значимого бита [1][2][3][4] основывается на нечувствительности человеческого глаза к малым изменениям оттенков синего цвета. Поэтому подмена младших битов у пикселей в синем канале на скрытые данные не может быть обнаружена при визуальном анализе картинки. ...
This study suggests a steganographic algorithm for embedding data in SVG images integrated into html code. The algorithm uses a composite key that includes an embed key, an encryption key, and a replacement table. The basic principle of embedding is to add style classes to an SVG image. These classes do not affect the picture in the browser. The message is encoded as the names of the classes to be added. Class names are formed based on a symmetric encryption algorithm and a replacement table. One class name contains 9 bits of information. A style set is generated for each added class. The new styles do not affect the appearance of the picture. Style settings are defined either based on default values or based on existing classes. Embed labels are added to tags with embedded data. The labels are calculated based on the hash functions from the string from the embedding key and the block number. Embedded data is randomly distributed over the code of an html page with SVG images. This arrangement makes it difficult to analyze the page when hacking the system. Embedded information is detected by sequential analysis of page code and search for embed marks. The sender of the message must have a permission to edit the web page. The recipient retrieves the message in page code view. An analysis of possible attacks on the proposed system has been carried out. Hacking of the system is possible only by direct overhauling. The system is resilient with the correct choice of hash function and encryption algorithm. The proposed steganographic embedding method is effective for html pages containing a fairly large number of SVG images.
... Several public datasets are used to evaluate our methodology. Therefore, measuring performance is one of the main aspects for ensuring the image quality was preserved to make sure that the image was not in our steganography technique, we also offer a thorough steganalysis [15]. ...
... Less of a difference exists between the two images when MSE is lower. Additionally, a lower MSE reflects greater stego picture quality, transparency, and security as it shows the pixel-by-pixel difference between the cover image and stego image [15]. ...
... When the denominators go close to 0, the method is stabilised using the constants C1 and C2. A local window is used to calculate these data [15]. ...
Lately, people are relying on the internet, so it is crucial for them to have a technique for controlling the usage of digital content, such as software, music, movies, and e-books. It restricts access to content by encrypting it and using technological tools like encryption keys and digital signatures. Steganography is used to hide messages and keep them from being intercepted. Steganography and cryptography are combined to provide a higher level of security by using LSB embedding using palindrome sequence. The proposed scheme used image dimensions of 512*512 pixels. The proposed solution performs in a comparable manner in its counterparts in the literature. Presented on Lena, Mandrill, Peppers and House 2 to be compared to other schemes.
