Strengthening steganoghraphy by using crow search algorithm of fingerprint image

In image steganography, secret communication is implemented to hide secret information into the cover image (used as the carrier to embed secret information) and generate a stego-image (generated image carrying hidden secret information).Nature provides many ideas for computer scientists. One of these ideas is the orderly way in which the organisms work in nature when they are in groups. If the group itself is treated as an individual (the swarm), the swarm is more intelligent than any individual in the group. Crow Search Algorithm (CSA) is a meta-heuristic optimizer where individuals emulate the intelligent behavior in a group of crows. It is based on simulating the intelligent behavior of crow flocks and attempts to imitate the social intelligence of a crow flock in their food gathering process. This paper presents a novel meta-heuristic approach based on the Crow Search Algorithm (CSA), where at the beginning the color cover image is converted into three channels (RGB) and then those channels are converted into three spaces, which are Y, Cb, Cr. After applying Discrete wavelet transform (DWT) on each space separately, the CSA algorithm is used on each space (YCbCr) to find the best location that will be used to hide secret information, the CSA is used to increase the security force by finding the best locations that have high frequency and are invulnerable to attacks, the DWT is used to increase robustness against noise. The proposed system is implemented on three fingerprint cover images for experiments, for the quality of stego image the histogram, Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Number of Pixel Change Rate Test (NPCR), Structural Similarity Index Metric (SSIM) and Correlation Coefficients (CC) are computed. The result demonstrated the strength of the CSA to hide data, also discovered that using CSA may lead to finding favorable results compared to the other algorithm

Strengthening steganoghraphy by using crow search algorithm of fingerprint image

In image steganography, secret communication is implemented to hide secret information into the cover image (used as the carrier to embed secret information) and generate a stego-image (generated image carrying hidden secret information).Nature provides many ideas for computer scientists. One of these ideas is the orderly way in which the organisms work in nature when they are in groups. If the group itself is treated as an individual (the swarm), the swarm is more intelligent than any individual in the group. Crow Search Algorithm (CSA) is a meta-heuristic optimizer where individuals emulate the intelligent behavior in a group of crows. It is based on simulating the intelligent behavior of crow flocks and attempts to imitate the social intelligence of a crow flock in their food gathering process. This paper presents a novel meta-heuristic approach based on the Crow Search Algorithm (CSA), where at the beginning the color cover image is converted into three channels (RGB) and then those channels are converted into three spaces, which are Y, Cb, Cr. After applying Discrete wavelet transform (DWT) on each space separately, the CSA algorithm is used on each space (YCbCr) to find the best location that will be used to hide secret information, the CSA is used to increase the security force by finding the best locations that have high frequency and are invulnerable to attacks, the DWT is used to increase robustness against noise. The proposed system is implemented on three fingerprint cover images for experiments, for the quality of stego image the histogram, Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Number of Pixel Change Rate Test (NPCR), Structural Similarity Index Metric (SSIM) and Correlation Coefficients (CC) are computed. The result demonstrated the strength of the CSA to hide data, also discovered that using CSA may lead to finding favorable results compared to the other algorithm

Recent Advances in Steganography

Steganography is the art and science of communicating which hides the existence of the communication. Steganographic technologies are an important part of the future of Internet security and privacy on open systems such as the Internet. This book's focus is on a relatively new field of study in Steganography and it takes a look at this technology by introducing the readers various concepts of Steganography and Steganalysis. The book has a brief history of steganography and it surveys steganalysis methods considering their modeling techniques. Some new steganography techniques for hiding secret data in images are presented. Furthermore, steganography in speeches is reviewed, and a new approach for hiding data in speeches is introduced

Blind colour image watermarking techniques in hybrid domain using least significant bit and slantlet transform

Colour image watermarking has attracted a lot of interests since the last decade in tandem with the rapid growth of internet and its applications. This is due to increased awareness especially amongst netizens to protect digital assets from fraudulent activities. Many research efforts focused on improving the imperceptibility or robustness of both semi-blind and non-blind watermarking in spatial or transform domain. The results so far have been encouraging. Nonetheless, the requirements of the watermarking applications are varied in terms of imperceptibility, robustness and capacity. Ironically, limited studies concern on the authenticity and blind watermarking. Hence, this study presents two new blind RGB image watermarking techniques called Model1 and Model2 in hybrid domain using Least Significant Bit (LSB) insertion and Slantlet Transform (SLT). The models share similar pre-processing and LSB insertion stages but differ in SLT approach. In addition, two interrelated watermarks known as main watermark (MW) and sub-watermark (SW) are also utilized. Firstly, the RGB cover image is converted into YCbCr colour space and then split up into three components namely, Y, Cb and Cr. Secondly, the Cb component is selected as a cover for the MW embedding using the LSB substitution to attain a Cb-watermarked image (CbW). Thirdly, the Cr component is chosen and converted into the transform domain using SLT, and is subsequently decomposed into two paths: three-level sub-bands for Model1 and two-level sub-bands for Model2. For each model, the sub-bands are then used as a cover for sub-watermark embedding to generate a Cr-watermarked image (CrW). Following that, the Y component, CbW and CrW are combined to obtain a YCbCr-watermarked image. Finally, the image is reverted to RGB colour space to attain the actual watermarked image (WI). Upon embedding, the MW and SW are extracted from WI. The extraction process is similar to the above embedding except it is accomplished in a reverse order. Experimental results which utilized the standard dataset with fifteen well-known attacks revealed that, among others: Model1 has produced high imperceptibility, moderate robustness and good capacity, with Peak Signal-to-Noise Ratio (PSNR) rose to 65dB, Normalized Cross Correlation (NCC) moderated at 0.80, and capacity was 15%. Meanwhile, Model2, as per designed, performed positively in all aspects, with NCC strengthened to 1.00, capacity jumped to 25% and PSNR softened at 55dB but still on the high side. Interestingly, in terms of authenticity, Model2 performed impressively albeit the extracted MW has been completely altered. Overall, the models have successfully fulfilled all the research objectives and also markedly outperformed benchmark watermarking techniques

An iterative algorithm for color space optimization on image segmentation

This paper proposes, a novel hybrid color component (HCC) issued from amounts number of color space with iterative manner, in fact traditional images obtained by RGB sensor weren’t the effective way in image processing applications, for this purpose we have propose a supervised algorithm to substitute RGB level by hybrid and suitable color space at the aim to make well representation of the handled amounts of data, this step is extremely important because the obtained results it will be injected in many future studies like tracking, classification, steganography and cryptography. The second part of this paper consists to segment image coded in hybrid color space already selected, the used algorithm is inspired from kernel function where statistical distribution was used to model background and Bayes rule to make decision of the membership of each pixel, in this research topics we have extended this algorithm in the aim to improve compactness of these distribution. Cauchy background modeling and subtraction is used, and shows the high accuracy of automatic player detection

Efficient and Robust Video Steganography Algorithms for Secure Data Communication

Over the last two decades, the science of secretly embedding and communicating data has gained tremendous significance due to the technological advancement in communication and digital content. Steganography is the art of concealing secret data in a particular interactive media transporter such as text, audio, image, and video data in order to build a covert communication between authorized parties. Nowadays, video steganography techniques are important in many video-sharing and social networking applications such as Livestreaming, YouTube, Twitter, and Facebook because of noteworthy developments in advanced video over the Internet. The performance of any steganography method, ultimately, relies on the imperceptibility, hiding capacity, and robustness against attacks. Although many video steganography methods exist, several of them lack the preprocessing stages. In addition, less security, low embedding capacity, less imperceptibility, and less robustness against attacks are other issues that affect these algorithms. This dissertation investigates and analyzes cutting edge video steganography techniques in both compressed and raw domains. Moreover, it provides solutions for the aforementioned problems by proposing new and effective methods for digital video steganography. The key objectives of this research are to develop: 1) a highly secure video steganography algorithm based on error correcting codes (ECC); 2) an increased payload video steganography algorithm in the discrete wavelet domain based on ECC; 3) a novel video steganography algorithm based on Kanade-Lucas-Tomasi (KLT) tracking and ECC; 4) a robust video steganography algorithm in the wavelet domain based on KLT tracking and ECC; 5) a new video steganography algorithm based on the multiple object tracking (MOT) and ECC; and 6) a robust and secure video steganography algorithm in the discrete wavelet and discrete cosine transformations based on MOT and ECC. The experimental results from our research demonstrate that our proposed algorithms achieve higher embedding capacity as well as better imperceptibility of stego videos. Furthermore, the preprocessing stages increase the security and robustness of the proposed algorithms against attacks when compared to state-of-the-art steganographic methods

Automatic region selection method to enhance image-based steganography

Image-based steganography is an essential procedure with several practical applications related to information security, user authentication, copyright protection, etc. However, most existing image-based steganographic techniques assume that the pixels that hide the data can be chosen freely, such as random pixel selection, without considering the contents of the input image. So, the “region of interest” such as human faces in the input image might have defected after data hiding even at a low inserting rate, and this will degrade the visual quality especially for the images containing several human faces. With this view, we proposed a novel approach that combines human skin-color detection along with the LSB approach which can choose the embedding regions. The idea behind that is based on the fact that the Human Vision System HVS tends to focus its attention on selectively certain structures of the visual scene instead of the whole image. Practically, human skin-color is good evidence of the existence of human targets in images. To the best of our knowledge, this is the first attempt that employs skin detection in application to steganography which consider the contents of input image and consequently can choose the embedding regions. Moreover, an enhanced RSA algorithm and Elliptic Curve Equation are used to provide a double level of security. In addition, the system embeds noise bits into the resulting stego-image to make the attacker’s task more confusing. Two datasets are used for testing and evaluation. The experimental results show that the proposed approach achieves a significant security improvement with high image quality

SYNTEZA OPTYMALNEJ METODY STEGANOGRAFII WEDŁUG WYBRANYCH KRYTERIÓW

One of the steganography areas is digital watermarking. In this paper, the technique of comparative analysis of embedding information methods into an image was proposed. A comprehensive analysis of the most relevant steganographic methods of hiding information was made. Own method of embedding information in still images was synthesized. The possibility of studied methods to adapt to the real channels was evaluated for the first time. The robustness and security of steganographic systems based on the proposed method were also demonstrated.Jednym z obszarów steganografii jest osadzanie cyfrowych znaków wodnych. W niniejszej pracy zaproponowano metodykę analizy porównawczej metod osadzania informacji w obrazach. Została dokonana wszechstronna analiza najnowszych metod ukrywania informacji za pomocą steganografii. Opracowano własną metodę osadzania informacji w nieruchomych obrazach. Oceniono możliwość adaptowania się metod do charakterystyk rzeczywistych kanałów komunikacyjnych. Wykazano wiarygodność i bezpieczeństwo systemów steganograficznych wykorzystujących proponowaną metodę