Resulting Stego Image Research Articles

An image steganography algorithm via a compression and chaotic maps

Steganography is widely recognized as an effective method for protecting information via digital media. This paper presents an innovative image steganography algorithm incorporating image compression, chaotic maps, and the least significant bit. The process begins with the compression of a confidential medical image using Huffman encoding. The compressed image then undergoes shuffling, facilitated by the chaotic logistic map. The bits from the shuffled image are discreetly embedded into randomly selected pixels of the cover image, guided by the chaotic piecewise smooth map. The resulting stego image is generated. Statistical analyses are applied to both the cover and stego images for evaluation. The proposed algorithm is compared against state-of-the-art algorithms, and the results demonstrate its superiority over existing methods.

DISH: Digital image steganography using stochastic-computing with high-capacity

Stochastic computing is a relatively new approach to computing that has gained interest in recent years due to its potential for low-power and high-noise environments. It is a method of computing that uses probability to represent and manipulate data, therefore it has applications in areas such as signal processing, machine learning, and cryptography. Stochastic steganography involves hiding a message within a cover image using a statistical model. Unlike traditional steganography techniques that use deterministic algorithms to embed the message, stochastic steganography uses a probabilistic approach to hide the message in a way that makes it difficult for an adversary to detect. Due to this error robustness and large bit streams stochastic computing, they are well suited for high capacity and secure image steganography. In this paper, as per the authors’ best knowledge, image steganography using stochastic computing based on linear feedback shift register (LFSR) is proposed for the first time. In the proposed technique, the cover image is converted to stochastic representation instead of the binary one, and then a secret image is embedded in it. The resulting stego image has a high PSNR value transmitted with no visual trace of the hidden image. The final results are stego image with PSNR starting from 30 dB and a maximum payload up to 40 bits per pixel (bpp) with an effective payload up to 28 bpp. The proposed method achieves high security and high capability of the number of stored bits in each pixel. Thus, the proposed method can prove a vital solution for high capacity and secure image steganography, which can then be extended to other types of steganography.

Enhancing Least Significant Bit Steganography Image Fidelity Using Brotli Compression

The rapid growth of technology has provided extensive convenience and openness in accessing information, yet this hasn't been balanced with an equivalent enhancement in information security. Steganography plays a crucial role in concealing and protecting data, with the Least Significant Bit (LSB) method being a commonly used algorithm that operates by substituting the least significant bits in the image pixels with the bits of the data to be hidden, aiming to preserve the image quality. This research aims to enhance the quality of the steganography result using LSB by employing the Brotli compression technique, coupled with increasing image's capacity. Brotli compression aims to reduce the size of the resulting stego image by combining embedded data that share identical values. Experiment results will be obtained by comparing the original image with the stego image using metrics like Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Structural Similarity Index (SSIM). The experiments successfully demonstrated that the integration of LSB with Brotli compression outperformed the regular LSB method, showing a 6.64% increase in PSNR, followed by a decrease in MSE by approximately 63.79%, and an increase in SSIM by around 0.0039%. This was accompanied by a continuous increase in compression values depending on the input data size. These results indicate that the integration of LSB with Brotli compression was successfully implemented to enhance the fidelity of the stego image

PENGAMANAN DATA DIGITAL MENGGUNAKAN TEKNIK INTEGER WAVELET TRANSFORM DAN LEAST SIGNIFICANT BIT

AbstractData is an asset for all parties. So that it must always be guarded or secured so that it is not misused by irresponsible parties. One of the methods used for data security is steganography. In this paper, efforts to secure data are discussed through the development of steganographic algorithms using the Haar integer wavelet transform (IWT-Haar) and least significant bit (LSB) techniques to hide secret messages in the form of digital text into digital images (cover images) to produce stego images. The results show that the extracting process is much faster than the embedding process. The PSNR values obtained ranged from 55-71,5 dB (far greater than 40 dB). This shows that the resulting stego image is of very good quality. In plain view, the difference between the cover image and the stego image has not changed significantly.Key words: digital image, embedding, extraction, Haar integer wavelet transform, steganographyÂ

Asymmetric Data Hiding for Compressed Images with High Payload and Reversibility

Hiding secret data in digital images is an attractive topic in the information security research area. Because the data-embedded stego image looks exactly the same as a regular image, transmitting secret data with stego images does not draw the attention of eavesdroppers, thus fulfilling the goal of information security. Many reversible data hiding (RDH) methods for absolute moment block truncation coding (AMBTC) compressed images have been proposed. These methods hide secret data in an AMBTC-compressed image to produce a stego image and transmit it to the recipient. Upon receiving the stego image, the recipient can extract the secret data and recover the AMBTC-compressed image. In this paper, we propose an RDH scheme for AMBTC-compressed images with an asymmetric embedding rule. Using the AMBTC-compressed version as the basis, the proposed embedding scheme always modifies a pixel value toward its original value with a step size (bitrate) proportional to the gap width. Therefore, the visual quality of the stego image is better than the referred AMBTC version. Additionally, as a result of the adaptive bitrate strategy, the data embedding capacity of the proposed scheme outperforms that of state-of-the-art methods. The security of the resulting stego images was also tested by RS-steganalysis. Experimental results show that the overall performance of the proposed scheme is satisfactory. We revised it, please confirm.

Secure high payload steganography: A model-based approach

The strong energy compaction property of the Discrete Cosine Transform (DCT) has inspired DCT-based steganography techniques to embed secret data in large areas of the insignificant DCT coefficients. Since these coefficients are noncritical, conventional DCT-based steganography techniques replace these insignificant coefficients with the secret data. This basic idea has enabled DCT-based steganography techniques to hide a substantial amount of secret data while maintaining acceptable stego fidelity. However, because these insignificant DCT coefficients do still contribute to the overall quality of the resulting stego image in the spatial domain, there will be an advantage in retaining them as much as possible. Thus, to optimize the stego quality, this paper proposes a novel hiding strategy where the general structure of the insignificant DCT coefficients is retained. A model-based technique is developed using polynomial surface-fitting of the insignificant DCT coefficients, and the secret data is superimposed on the polynomial-modeled coefficients, thus producing a stego image that does not compromise the overall structure of the original cover image. Experimental results demonstrating improvements in the stego quality and security levels of the proposed steganography technique in comparison to state-of-the-art schemes are presented.

Covert and Secure Communication Using Multiple Invisible Stego Images by Split-Logical Algorithm

The use of the web is developing for surreptitious and non-surreptitious communication with the expansion of brilliant innovations. In this circumstance, there is a need to improve the security level of the covert information. Our motive is to propose a unique algorithm by using steganography along with cryptography which provides a better solution for secret communication and improves security with more levels. In this paper, the two-level stationary wavelet transform technique is applied to cover image to acquire HH2 sub-band alongside the remaining sub-bands. The data are implanted into the HH2 sub-band of the cover image by utilizing the random pixel embedded strategy to accomplish the stego image. To improve the security of the stego image, the surreptitious text data are changed into cipher form with a novel cryptography algorithm that incorporates unique data conversion and gray-code techniques. The resultant stego image undergoes to split-logical algorithm to create numerous imperceptible stego images. The main purpose of imperceptible stego images is to provide better security to covert information and also it increases the payload capacity. The concept of generating imperceptible stego images is, each of them will be treated as a stego image for hackers. But original stego image is reconstructed by combining all generated imperceptible stego images. These imperceptible stego images are ready to oppose the diverse steganalysis assaults like visual, noise, rotational assaults, and so forth.

A High-Capacity Image Steganography Method Using Chaotic Particle Swarm Optimization

Image steganography has been widely adopted to protect confidential data. Researchers have been seeking to improve the steganographic techniques in order to increase the embedding capacity while preserving the stego-image quality. In this paper, we propose a steganography method using particle swarm optimization and chaos theory aiming at finding the best pixel locations in the cover image to hide the secret data while maintaining the quality of the resultant stego-image. To enhance the embedding capacity, the host and secret images are divided into blocks and each block stores an appropriate amount of secret bits. Experimental results show that the proposed scheme outperforms existing methods in terms of the PSNR and SSIM image quality metrics.

A Novel Hybrid Image Hiding Technique using Elliptic Curve Cryptography and DNA Computing Technique

The proposed novel hybrid image hiding techniques uses the security features of ECC for encrypting the secret image before embedding with cover image and also map the secret image with DNA nucleotide to improve the level of security with high embedding capacity. In the proposed image steganography, the secret image is fed as input to the ECC encryption algorithm and the resultant ciphertext point is mapped with DNA nucleotide, and then converts it into binary digits. Second, the cover image is compressed by using DWT compression techniques. The compressed image is used as a cover image to embed the secret image by using a singular value decomposition algorithm. The resultant stego image will have high PSNR and less MSE. Results show that 36.23% decreased value of MSE value and 5.6% increased value of PSNR for 512 × 512 image size.

Coverless Image Steganography Based on Optical Mark Recognition and Machine Learning

The most significant factor to consider during private information transmission through the internet (i.e., insecure channel) is security. So, to keep this data from unauthorized access during transmission, steganography is used. Steganography is the scheme of securing sensitive information by concealing it within carriers such as digital images, videos, audio, text, etc. Current image steganography methods work as follows; it assigns cover image then embeds the secret message within it by pixels' modifications, creating the resultant stego-image. These modifications allow steganalysis algorithms to detect the embedded secret message. So, a coverless data hiding concept is proposed to solve this problem. Coverless does not mean that the secret message will be transmitted without using a cover file, or the cover file can be discarded. Instead, the secret message will be embedded by generating a cover file or a secret message mapping. In this paper, a novel, highly robust coverless image steganography method based on optical mark recognition (OMR) and rule-based machine learning (RBML) is proposed.

Quality Factor terhadap Kapasitas Pesan Rahasia pada Steganografi Citra JPEG dan Kualitas Citra Stego

One of the container media that is available and popular is the Joint Photographic Experts Group (JPEG) format image. This article aims to determine the effect of Quality Factor on the secret message capacity of JPEG image steganography and stego image quality. The quality of an image can actually be seen subjectively with the human eye, but this is relative between each individual. Because the assessment of the human eye varies from person to person. In addition, the effect of Quality Factor on secret message capacity is not yet known whether it has an impact. Therefore, in this study the Quality Factor is used to objectively see the secret message capacity of the JPEG image steganography and the quality of the stego image. The parameter used to determine the quality of an image is the Peak Signal to Noise Ratio (PSNR). PSNR will compare the quality of the original image (before steganography) with the stego image. The test results show that the Q Factor effect can affect the secret message capacity of the JPEG image steganography and the stego image quality. The bigger the Q Factor, the more the message capacity is generated. The greater the Q factor, the better the quality of the resulting stego image.

Stego-chain: A framework to mine encoded stego-block in a decentralized network

Traditional image steganography conceals secret data into the cover image and then transmits the resulting stego-image to the intended recipient via an insecure channel. The intruders try to sense the channel but cannot easily find any clues regarding the concealed data since both cover and stego images are seemingly indistinguishable. However, the key concern is the integrity of the stego image as an intruder has the ability to intercept image so as to hamper the secret communication. To address this issue, we have introduced a blockchain based framework named “Stego-chain” which utilizes an efficient steganographic scheme based on dilated Robert’s edge detection. The aim of the said scheme is to expand the edge area so as to increase the embedding payload. The resulting stego image is encrypted through a shared secret key and then broadcasted in the form of chunk of frames across the valid nodes. The receiver accepts the tampered free frames, re-constructs the stego image through the shared secret key and then recovers the secret data through extraction procedure. Simulation results ensured that the proposed scheme offers higher payload than the state-of-the-art methods with considerable distortion in the stego image.

A modified LSB image steganography method using filtering algorithm and stream of password

ABSTRACT Data is one of the most significant assets nowadays and needs to address correctly in the growing risk of cybersecurity. Additionally, every year, data is stolen and modified from the internet when transmitting. Therefore, to improve security while transmission, there are two techniques available called cryptography and steganography. In cryptography, the information is encrypted to ciphertexts using a private key, but the message’s existence is visible to others, no matter how unbreakable they are. On the other hand, steganography hides the secret data in an ordinary non-secret file to avoid visual detection. This paper proposed a new data hiding method using LSB image steganography, where confidential information uses only the selected image pixel. For that, image pixel information is used to filter the complete image to decide the candidate pixel, and a user-defined password is used to secure the LSB steganography. For better security, before applying steganography, the AES method encrypts the secret message. In the experiment, MSE and PSNR value are measured to assess the quality of the resultant stego image. The stego image provides higher PSNR and less MSE value as compared to other studied methods, which illustrate the flexibility of the proposed method.

Using Chaotic Stream Cipher to Enhance Data Hiding in Digital Images

The growing potential of modern communications needs the use of secure means to protect information from unauthorized access and use during transmission. In general, encryption a message using cryptography techniques and then hidden a message with a steganography methods provides an additional layer of protection. Furthermore, using these combination reduces the chance of finding the hidden message. This paper proposed a system which combines schemes of cryptography with steganography for hiding secret messages and to add more complexity for steganography. The proposed system secret message encoded with chaotic stream cipher and afterwards the encoded data is hidden behind an RGB or Gray cover image by modifying the kth least significant bits (k-LSB) of cover image pixels. The resultant stego-image less distorters. After which can be used by the recipient to extract that bit-plane of the image. In fact, the schemes of encryption/decryption and embedding/ extracting in the proposed system depends upon two shred secret keys between the sender and the receiver. An experiment shows that using an unauthorized secret keys between the sender and the receiver have totally different messages from the original ones which improve the confidentiality of the images.

A novel local binary pattern based blind feature image steganography

Steganography methods in general terms tend to embed more and more secret bits in the cover images. Most of these methods are designed to embed secret information in such a way that the change in the visual quality of the resulting stego image is not detectable. There exists some methods which preserve the global structure of the cover after embedding. However, the embedding capacity of these methods is very less. In this paper a novel feature based blind image steganography technique is proposed, which preserves the LBP (Local binary pattern) feature of the cover with comparable embedding rates. Local binary pattern is a well known image descriptor used for image representation. The proposed scheme computes the local binary pattern to hide the bits of the secret image in such a way that the local relationship that exists in the cover are preserved in the resulting stego image. The performance of the proposed steganography method has been tested on several images of different types to show the robustness. State of the art LSB based steganography methods are compared with the proposed method to show the effectiveness of feature based image steganography

A new encrypted method in image steganography

<p>Steganography is data hiding technique in internet. Here we send CAPTCHA codes within a cover image using Image steganography. CAPTCHA are the crazy codes. They are used in human response test. The word is actually an acronym for: "<strong>C</strong>ompletely <strong>A</strong>utomated <strong>P</strong>ublic <strong>T</strong>uring test to tell <strong>C</strong>omputers and <strong>H</strong>umans <strong>A</strong>part". It is a type of challenge–response test used in computing to determine whether or not the user is a human. Websites implement CAPTCHA codes into their registration processes due to spam. This is the utility of CAPTCHA codes. Here we generate CAPTCHA codes and later send them in an encrypted version. So, actually CAPTCHA codes are embedded into cover image with an encrypted form resulting stego image and thus attackers cannot fetch the actual CAPTCHA resulting in a secured transmission of confidential data using image steganography.</p>

An Optimized Steganography Hiding Capacity and Imperceptibly Using Genetic Algorithms

In stenography, embedding data within an image has a trade-off between image quality and embedding capacity. Specifically, the more data are concealed within a carrier image, the further distortion the image suffers, causing a decline in the resultant stego image quality. Embedding high capacity of data into an image while preserving the quality of the carrier image can be seen as an optimization problem. In this paper, we propose a novel spatial steganography scheme using genetic algorithms (GAs). Our scheme utilizes new operations to increase least significant bits (LSB) matching between the carrier and the stego image which results in increased embedding capacity and reduced distortion. These operations are optimized pixel scanning in vertical and horizontal directions, circular shifting, flipping secret bits and secret data transposing. We formulate a general GA-based steganography model to search for the optimum solutions. Finally, we use LSB substitution for data embedding. We conduct extensive experimental testing of the proposed scheme and compare it to the state-of-art steganography schemes. The proposed scheme outperforms the relevant GA-based steganography methodologies.

Visual fidelity without sacrificing capacity: an adaptive Laplacian pyramid approach to information hiding

This paper investigates the improvements in hiding capacity and perceptibility of image-based steganography using a hiding scheme which utilizes a multiscale Laplacian pyramid of the cover image and the discrete cosine transform (DCT). The proposed methodology allows for an enhanced visual quality of the resulting stego image, while allowing for very high embedding payload capacities, which improves security by reducing an eavesdropper’s ability to detect and successively extract or change the hidden information. The basic idea is to hide the secret data in the DCT of the lowest level of the Laplacian pyramid of the cover image. This scheme employs a curve-fitting adaptive region approach in the DCT domain for enhanced visual fidelity as well as very high capacities as compared to competing methods. This paper also compares the embedding capacities of various steganography schemes that have been recently published in the literature. Experimental results confirm that the proposed hiding scheme can maintain consistently high stego image quality, in comparison to other spatial and frequency-domain schemes, when hiding at extremely high payload capacities.

Identification of cheaters in elections using steganography

This paper presents a new secret sharing scheme for identification of cheaters in the elections. In a proposed scheme secret image (voter ID) is embedded into cover image (Indian emblem) of same size and generates n stego images. The resulting stego images are visually good and look like a cover image. Various image quality metrics are used to assess the quality of stego images. Out of n stego images only last two stego images are required to reconstruct the secret and cover images without any loss. The proposed scheme offers high embedding capacity. Experimental results of proposed scheme shown to be superior in terms of PSNR and visual quality than existing schemes.

Steganography based image sharing with reversibility

Steganography is an art of hiding secret information in another information. The use of steganography is to maintain a covert communication between two parties. A (t, n) thresh-old secret sharing scheme is one popular method of implementing steganography. In this method, the secret image is distributed among n participants. Any t (or more) out of n authorized participants can recover the secret image and less than t participants cannot recover the secret image. In the proposed method, both secret and cover images are retrieved without any loss of information is called reversibility. The shadows can be successfully embedded in the cover image. The resulting stego images are visually good. Various image quality metrics are used to assess the quality of the stego images. The proposed scheme is efficient in terms of embedding capacity and is computationally faster compared to Pei-y.u et al., and other methods.