Biblio

The success of deep learning based steganography has shifted focus of researchers from traditional steganography approaches to deep learning based steganography. Various deep steganographic models have been developed for improved security, capacity and invisibility. In this work a multi-data deep learning steganography model has been developed using a well known deep learning model called Generative Adversarial Networks (GAN) more specifically using deep convolutional Generative Adversarial Networks (DCGAN). The model is capable of hiding two different messages, meant for two different receivers, inside a single cover image. The proposed model consists of four networks namely Generator, Steganalyzer Extractor1 and Extractor2 network. The Generator hides two secret messages inside one cover image which are extracted using two different extractors. The Steganalyzer network differentiates between the cover and stego images generated by the generator network. The experiment has been carried out on CelebA dataset. Two commonly used distortion metrics Peak signal-to-Noise ratio (PSNR) and Structural Similarity Index Metric (SSIM) are used for measuring the distortion in the stego image The results of experimentation show that the stego images generated have good imperceptibility and high extraction rates.

Transmitting data through the internet may have severe security risks due to illegal access done by attackers. Some methods have been introduced to overcome this issue, such as cryptography and steganography. Nevertheless, some problems still arise, such as the quality of the stego data. Specifically, it happens if the stego is shared with some users. In this research, a shared-secret mechanism is combined with steganography. For this purpose, the fuzzy logic edge detection and Prediction Error (PE) methods are utilized to hide private data. The secret sharing process is carried out after data embedding in the cover image. This sharing mechanism is performed on image pixels that have been converted to PE values. Various Peak Signal to Noise Ratio (PSNR) values are obtained from the experiment. It is found that the number of participants and the threshold do not significantly affect the image quality of the shares.

Watermarking is one of the most common data hiding techniques for multimedia elements. Broadcasting, copy control, copyright protection and authentication are the most frequently used application areas of the watermarking. Secret data can be embedded into the cover image with changing the values of the pixels in spatial domain watermarking. In addition to this method, cover image can be converted into one of the transformation such as Discrete Wavelet Transformation (DWT), Discrete Cousin Transformation (DCT) and Discrete Fourier Transformation (DFT). Later on watermark can be embedded high frequencies of transformation coefficients. In this work, cover image transformed one, two and three level DWT decompositions. Binary watermark is hided into the low and high frequencies in each decomposition. Experimental results show that watermarked image is robust, secure and resist against several geometric attacks especially JPEG compression, Gaussian noise and histogram equalization. Peak Signal-to-Noise Ratio (PSNR) and Similarity Ratio (SR) values show very optimal results when we compare the other frequency and spatial domain algorithms.

In our time the rapid growth of internet and digital communications has been required to be protected from illegal users. It is important to secure the information transmitted between the sender and receiver over the communication channels such as the internet, since it is a public environment. Cryptography and Steganography are the most popular techniques used for sending data in secrete way. In this paper, we are proposing a new algorithm that combines both cryptography and steganography in order to increase the level of data security against attackers. In cryptography, we are using affine hill cipher method; while in steganography we are using Hybrid edge detection with LSB to hide the message. Our paper shows how we can use image edges to hide text message. Grayscale images are used for our experiments and a comparison is developed based on using different edge detection operators such as (canny-LoG ) and (Canny-Sobel). Their performance is measured using PSNR (Peak Signal to Noise ratio), MSE (Mean Squared Error) and EC (Embedding Capacity). The results indicate that, using hybrid edge detection (canny- LoG) with LSB for hiding data could provide high embedding capacity than using hybrid edge detection (canny- Sobel) with LSB. We could prove that hiding in the image edge area could preserve the imperceptibility of the Stego-image. This paper has also proved that the secrete message was extracted successfully without any distortion.

This paper proposes 2 multiple layer message security schemes. Information security is carried out through the implementation of cryptography, steganography and image processing techniques. In both schemes, the sensitive data is first encrypted by employing a chaotic function. In the first proposed scheme, LSB steganography is then applied to 2D slices of a 3D image. In the second proposed scheme, a corner detection filter is first applied to the 2D slices of a 3D image, then LSB embedding is carried out in those corner-detected pixels. The number of neighboring pixels used for corner detection is varied and its effect is noted. Performance of the proposed schemes is numerically evaluated using a number of metrics, including the mean squared error (MSE), the peak signal to noise ratio (PSNR), the structure similarity index measure (SSIM), the normalized cross-correlation (NCC), the image fidelity (IF), as well as the image difference (ID). The proposed schemes exhibit superior payload capacity and security in comparison to their counterparts from the literature.

In the Internet of Things, it is more important than ever to effectively address the problem of secure transmission based on steganographic substitution by synthesizing digital sensor data. In this case, the degree to which the grayscale message is obscured is a necessary issue. To ensure information security in IoT systems, various methods are used and information security problems are solved to one degree or another. The article proposes a method and algorithm for a computer image in grayscale, in which the value of each pixel is one sample, representing the amount of light, carrying only information about the intensity. The proposed method in grayscale using steganographic coding provides a secure implementation of data transmission in the IoT system. Study results were analyzed using PSNR (Peak Signal to Noise Ratio).

In the course of the research, the research of discriminatory methods of handling video information resource based on the JPEG platform was carried out. This research showed a high interest of the scientific world in identifying important data at different phases of handling. However, the discriminatory handling of the video information resource after the quantization phase is not well understood. Based on the research data, the goal is to find possible ways to operation a video information resource based on a JPEG platform in order to identify important data in a telecommunications system. At the same time, the proposed strategies must provide the required pace of dynamic picture grade and hiding in the context of limited bandwidth. The fulfillment of the condition with limited bandwidth is achieved through the use of a lossless compression algorism based on arithmetic coding. The purpose of the study is considered to be achieved if the following requirements are met:1.Reduction of the volume of dynamic pictures by 30% compared to the initial amount;2.The quality pace is confirmed by an estimate of the peak signal-to-noise ratio for an authorized user, which is Ψauthor ≥ 20 dB;3.The pace of hiding is confirmed by an estimate of the peak signal-to-noise ratio for unauthorized access, which is Ψunauthor ≤ 9 dBThe first strategy is to use encryption tables. The advantage of this strategy is its high hiding strength.The second strategy is the important matrix method. The advantage of this strategy is higher performance.Thus, the goal of the study on the development of possible ways of handling a video information resource based on a JPEG platform in order to identify important data in a telecommunication system with the given requirements is achieved.

Digital watermarking is the multimedia leading security protection as it permanently escorts the digital content. Image copyright protection is becoming more anxious as the new 5G technology emerged. Protecting images with a robust scheme without distorting them is the main trade-off in digital watermarking. In this paper, a watermarking scheme based on discrete cosine transform (DCT) and singular value decomposition (SVD) using canny edge detector technique is proposed. A binary encrypted watermark is reshaped into a vector and inserted into the edge detected vector from the diagonal matrix of the SVD of DCT DC and low-frequency coefficients. Watermark insertion is performed by using an edge-tracing mechanism. The scheme is evaluated using the Peak Signal to Noise Ratio (PSNR) and Normalized Correlation (NC). Attained results are competitive when compared to present works in the field. Results show that the PSNR values vary from 51 dB to 55 dB.

IoT is an emerging technology in modern world of communication. As the usage of IoT devices is increasing in day to day life, the secure data communication in IoT environment is the major challenge. Especially, small sized Single-Board Computers (SBCs) or Microcontrollers devices are widely used to transfer data with another in IoT. Due to the less processing power and storage capabilities, the data acquired from these devices must be transferred very securely in order to avoid some ethical issues. There are many cryptography approaches are applied to transfer data between IoT devices, but there are obvious chances to suspect encrypted messages by eavesdroppers. To add more secure data transfer, steganography mechanism is used to avoid the chances of suspicion as another layer of security. Based on the capabilities of IoT devices, low complexity images are used to hide the data with different hiding algorithms. In this research study, the secret data is encoded through QR code and embedded in low complexity cover images by applying image to image hiding fashion. The encoded image is sent to the receiving device via the network. The receiving device extracts the QR code from image using secret key then decoded the original data. The performance measure of the system is evaluated by the image quality parameters mainly Peak Signal to Noise Ratio (PSNR), Normalized Coefficient (NC) and Security with maintaining the quality of contemporary IoT system. Thus, the proposed method hides the precious information within an image using the properties of QR code and sending it without any suspicion to attacker and competes with the existing methods in terms of providing more secure communication between Microcontroller devices in IoT environment.

In this paper, Reversible data hiding using difference statistics technique incorporating QR codes was proposed. Here, Quick Response (QR) codes were employed as an additional feature and were hidden in the corners of the original image to direct to the hyperlink after authentication and then embedding the secret data bits was carried out. At the receiver side, when the QR codes were scanned by the user, the link to the webpage was accessed, and then the original image and the secret data bits were recovered by using the proposed reversible data hiding scheme. In the proposed scheme, the pixels of the cover image were scanned in row-major order fashion, and the differences between the adjacent pixels were computed, keeping the first pixel unaltered to maintain the size of the host and the difference image same. Now, the histogram was shifted towards the right or left to reduce the redundancy and then to embed the secret data bits were done. Due to the similarity exists between the pixel values, the difference between the host and the secret image reconstructs the marked image. The proposed scheme was carried out using MATLAB 2013. PSNR (Peak Signal to Noise Ratio) and payload have been computed for various test images to validate the proposed scheme and found to be better than the available literature.

This paper proposes a steganography method using the digital images. Here, we are embedding the data which is to be secured into the digital image. Human Visual System proved that the changes in the image edges are insensitive to human eyes. Therefore we are using edge detection method in steganography to increase data hiding capacity by embedding more data in these edge pixels. So, if we can increase number of edge pixels, we can increase the amount of data that can be hidden in the image. To increase the number of edge pixels, multiple edge detection is employed. Edge detection is carried out using more sophisticated operator like canny operator. To compensate for the resulting decrease in the PSNR because of increase in the amount of data hidden, Minimum Error Replacement [MER] method is used. Therefore, the main goal of image steganography i.e. security with highest embedding capacity and good visual qualities are achieved. To extract the data we need the original image and the embedding ratio. Extraction is done by taking multiple edges detecting the original image and the data is extracted corresponding to the embedding ratio.

This paper proposes an advanced scheme of message security in 3D cover images using multiple layers of security. Cryptography using AES-256 is implemented in the first layer. In the second layer, edge detection is applied. Finally, LSB steganography is executed in the third layer. The efficiency of the proposed scheme is measured using a number of performance metrics. For instance, mean square error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), mean absolute error (MAE) and entropy.

Hiding information is a process to hide data or include it in different digital media such as image, audio, video, and text. However, there are many techniques to achieve the process of hiding information in the image processing, in this paper, a new method has been proposed for hidden data mechanism (which is a text file), then a transposition cipher method has been employed for encryption completed. It can be used to build an encrypted text and also to increase security against possible attacks while sending it over the World Wide Web. A genetic algorithm has been affected in the adjustment of the encoded text and DNA in the creation of an encrypted text that is difficult to detect and then include in the image and that affected the image visual quality. The proposed method outperforms the state of arts in terms of efficiently retrieving the embedded messages. Performance evaluation has been recorded high visual quality scores for the (SNR (single to noise ratio), PSNR (peak single to noise ratio) and MSE (mean square error).

Data Transmission in network security is one of the most vital issues in today's communication world. The outcome of the suggested method is outlined over here. Enhanced security can be achieved by this method. The vigorous growth in the field of information communication has made information transmission much easier. But this type of advancement has opened up many possibilities of information being snooped. So, day-by-day maintaining of information security is becoming an inseparable part of computing and communication. In this paper, the authors have explored techniques that blend cryptography & steganography together. In steganography, information is kept hidden behind a cover image. In this paper, approaches for information hiding using both cryptography & steganography is proposed keeping in mind two considerations - size of the encrypted object and degree of security. Here, signature image information is kept hidden into cover image using private key of sender & receiver, which extracts the information from stego image using a public key. This approach can be used for message authentication, message integrity & non-repudiation purpose.

With the rapid development of the Internet, preserving the security of confidential data has become a challenging issue. An effective method to this end is to apply steganography techniques. In this paper, we propose an efficient steganography algorithm which applies edge detection and MPC algorithm for data concealment in digital images. The proposed edge detection scheme partitions the given image, namely cover image, into blocks. Next, it identifies the edge blocks based on the variance of their corner pixels. Embedding the confidential data in sharp edges causes less distortion in comparison to the smooth areas. To diminish the imposed distortion by data embedding in edge blocks, we employ LSB and MPC algorithms. In the proposed scheme, the blocks are split into some groups firstly. Next, a full tree is constructed per group using the LSBs of its pixels. This tree is converted into another full tree in some rounds. The resultant tree is used to modify the considered LSBs. After the accomplishment of the data embedding process, the final image, which is called stego image, is derived. According to the experimental results, the proposed algorithm improves PSNR with at least 5.4 compared to the previous schemes.

Video Steganography is an extension of image steganography where any kind of file in any extension is hidden into a digital video. The video content is dynamic in nature and this makes the detection of hidden data difficult than other steganographic techniques. The main motive of using video steganography is that the videos can store large amount of data in it. This paper focuses on security using the combination of hybrid neural networks and hash function for determining the best bits in the cover video to embed the secret data. For the embedding process, the cover video and the data to be hidden is uploaded. Then the hash algorithm and neural networks are applied to form the stego video. For the extraction process, the reverse process is applied and the secret data is obtained. All experiments are done using MatLab2016a software.

Least Significant Bit (LSB) as one of steganography methods that already exist today is really mainstream because easy to use, but has weakness that is too easy to decode the hidden message. It is because in LSB the message embedded evenly to all pixels of an image. This paper introduce a method of steganography that combine LSB with clustering method that is Fuzzy C-Means (FCM). It is abbreviated with LSB\_FCM, then compare the stegano result with LSB method. Each image will divided into two cluster, then the biggest cluster capacity will be choosen, finally save the cluster coordinate key as place for embedded message. The key as a reference when decode the message. Each image has their own cluster capacity key. LSB\_FCM has disadvantage that is limited place to embedded message, but it also has advantages compare with LSB that is LSB\_FCM have more difficulty level when decrypted the message than LSB method, because in LSB\_FCM the messages embedded randomly in the best cluster pixel of an image, so to decrypted people must have the cluster coordinate key of the image. Evaluation result show that the MSE and PSNR value of LSB\_FCM some similiar with the pure LSB, it means that LSB\_FCM can give imperceptible image as good as the pure LSB, but have better security from the embedding place.

We present a gradient-based attack against SVM-based forensic techniques relying on high-dimensional SPAM features. As opposed to prior work, the attack works directly in the pixel domain even if the relationship between pixel values and SPAM features can not be inverted. The proposed method relies on the estimation of the gradient of the SVM output with respect to pixel values, however it departs from gradient descent methodology due to the necessity of preserving the integer nature of pixels and to reduce the effect of the attack on image quality. A fast algorithm to estimate the gradient is also introduced to reduce the complexity of the attack. We tested the proposed attack against SVM detection of histogram stretching, adaptive histogram equalization and median filtering. In all cases the attack succeeded in inducing a decision error with a very limited distortion, the PSNR between the original and the attacked images ranging from 50 to 70 dBs. The attack is also effective in the case of attacks with Limited Knowledge (LK) when the SVM used by the attacker is trained on a different dataset with respect to that used by the analyst.

For the increasing use of internet, it is equally important to protect the intellectual property. And for the protection of copyright, a blind digital watermark algorithm with SVD and OSELM in the IWT domain has been proposed. During the embedding process, SVD has been applied to the coefficient blocks to get the singular values in the IWT domain. Singular values are modulated to embed the watermark in the host image. Online sequential extreme learning machine is trained to learn the relationship between the original coefficient and the corresponding watermarked version. During the extraction process, this trained OSELM is used to extract the embedded watermark logo blindly as no original host image is required during this process. The watermarked image is altered using various attacks like blurring, noise, sharpening, rotation and cropping. The experimental results show that the proposed watermarking scheme is robust against various attacks. The extracted watermark has very much similarity with the original watermark and works good to prove the ownership.

Image encryption takes been used by armies and governments to help top-secret communication. Nowadays, this one is frequently used for guarding info among various civilian systems. To perform secure image encryption by means of various chaotic maps, in such system a legal party may perhaps decrypt the image with the support of encryption key. This reversible chaotic encryption technique makes use of Arnold's cat map, in which pixel shuffling offers mystifying the image pixels based on the number of iterations decided by the authorized image owner. This is followed by other chaotic encryption techniques such as Logistic map and Tent map, which ensures secure image encryption. The simulation result shows the planned system achieves better NPCR, UACI, MSE and PSNR respectively.

In this paper a novel data hiding method has been proposed which is based on Non-Linear Feedback Shift Register and Tinkerbell 2D chaotic map. So far, the major work in Steganography using chaotic map has been confined to image steganography where significant restrictions are there to increase payload. In our work, 2D chaotic map and NLFSR are used to developed a video steganography mechanism where data will be embedded in the segregated frames. This will increase the data hiding limit exponentially. Also, embedding position of each frame will be different from others frames which will increase the overall security of the proposed mechanism. We have achieved this randomized data hiding points by using a chaotic map. Basically, Chaotic theory which is non-linear dynamics physics is using in this era in the field of Cryptography and Steganography and because of this theory, little bit changes in initial condition makes the output totally different. So, it is very hard to get embedding position of data without knowing the initial value of the chaotic map.

Multimedia security and copyright protection has been a popular topic for research and application, due to the explosion of data exchange over the internet and the widespread use of digital media. Watermarking is a process of hiding the digital information inside a digital media. Information hiding as digital watermarks in multimedia enables protection mechanism in decrypted contents. This paper presents a comparative study of existing technique used for digital watermarking an image using Genetic Algorithm and Bacterial Foraging Algorithm (BFO) based optimization technique with proposed one which consists of Genetic Algorithm and Honey Bee based optimization technique. The results obtained after experiment conclude that, new method has indeed outperformed then the conventional technique. The implementation is done over the MATLAB.

Wireless Capsule Endoscopy (WCE) is a noninvasive device for detection of gastrointestinal problems especially small bowel diseases, such as polyps which causes gastrointestinal bleeding. The quality of WCE images is very important for diagnosis. In this paper, a new method is proposed to improve the quality of WCE images. In our proposed method for improving the quality of WCE images, Removing Noise and Contrast Enhancement (RNCE) algorithm is used. The algorithm have been implemented and tested on some real images. Quality metrics used for performance evaluation of the proposed method is Structural Similarity Index Measure (SSIM), Peak Signal-to-Noise Ratio (PSNR) and Edge Strength Similarity for Image (ESSIM). The results obtained from SSIM, PSNR and ESSIM indicate that the implemented RNCE method improve the quality of WCE images significantly.

Salt and Pepper Noise is very common during transmission of images through a noisy channel or due to impairment in camera sensor module. For noise removal, methods have been proposed in literature, with two stage cascade various configuration. These methods, can remove low density impulse noise, are not suited for high density noise in terms of visible performance. We propose an efficient method for removal of high as well as low density impulse noise. Our approach is based on novel extension over iterated conditional modes (ICM). It is cascade configuration of two stages - noise detection and noise removal. Noise detection process is a combination of iterative decision based approach, while noise removal process is based on iterative noisy pixel estimation. Using improvised approach, up to 95% corrupted image have been recovered with good results, while 98% corrupted image have been recovered with quite satisfactory results. To benchmark the image quality, we have considered various metrics like PSNR (Peak Signal to Noise Ratio), MSE (Mean Square Error) and SSIM (Structure Similarity Index Measure).

There are more and more systems using mobile devices to perform sensing tasks, but these increase the risk of leakage of personal privacy and data. Data hiding is one of the important ways for information security. Even though many data hiding algorithms have worked on providing more hiding capacity or higher PSNR, there are few algorithms that can control PSNR effectively while ensuring hiding capacity. In this paper, with controllable PSNR based on LSBs substitution- PSNR-Controllable Data Hiding (PCDH), we first propose a novel encoding plan for data hiding. In PCDH, we use the remainder algorithm to calculate the hidden information, and hide the secret information in the last x LSBs of every pixel. Theoretical proof shows that this method can control the variation of stego image from cover image, and control PSNR by adjusting parameters in the remainder calculation. Then, we design the encoding and decoding algorithms with low computation complexity. Experimental results show that PCDH can control the PSNR in a given range while ensuring high hiding capacity. In addition, it can resist well some steganalysis. Compared to other algorithms, PCDH achieves better tradeoff among PSNR, hiding capacity, and computation complexity.