Adopt an optimal location using a genetic algorithm for audio steganography

With the development of technologies, most of the users utilizing the Internet for transmitting information from one place to another place. The transmitted data may be affected because of the intermediate user. Therefore, the steganography approach is applied for managing the secret information. Here audio steganography is utilized to maintain the secret information by hiding the image into the audio files. In this work, discrete cosine transforms, and discrete wavelet transform is applied to perform the Steganalysis process. The optimal hiding location has been identified by using the optimization technique called a genetic algorithm. The method utilizes the selection, crossover and mutation operators for selecting the best location. The chosen locations are difficult to predict by unauthorized users because the embedded location is varied from information to information. Then the efficiency of the system ensures the high PSNR, structural similarity index (SSIM), minimum mean square error value and Jaccard, which is evaluated on the audio Steganalysis dataset

Secure Data Transfer through a Combination of Steganographic and Cryptographic Encryption Technique

Security for information has become a great concern in today’s internet era. Thus sending sensitive information from one end to another end via common communicating channel has become inevitable. Steganography has various useful applications and the technique employed depends on the requirements of the application to be designed for. For instance, applications may require absolute invisibility of the secret data, larger secret data to be hidden or high degree of robustness of the carrier. This paper aims at studying popular encryption techniques and their drawbacks due to which they could not be put to practical use along with a proposed method of successfully encrypting information both in image and text format combing their successful delivery to the destination using steganographic and cryptographic techniques of information encryption

Data hiding in multimedia - theory and applications

Multimedia data hiding or steganography is a means of communication using subliminal channels. The resource for the subliminal communication scheme is the distortion of the original content that can be tolerated. This thesis addresses two main issues of steganographic communication schemes: 1. How does one maximize the distortion introduced without affecting fidelity of the content? 2. How does one efficiently utilize the resource (the distortion introduced) for communicating as many bits of information as possible? In other words, what is a good signaling strategy for the subliminal communication scheme? Close to optimal solutions for both issues are analyzed. Many techniques for the issue for maximizing the resource, viz, the distortion introduced imperceptibly in images and video frames, are proposed. Different signaling strategies for steganographic communication are explored, and a novel signaling technique employing a floating signal constellation is proposed. Algorithms for optimal choices of the parameters of the signaling technique are presented. Other application specific issues like the type of robustness needed are taken into consideration along with the established theoretical background to design optimal data hiding schemes. In particular, two very important applications of data hiding are addressed - data hiding for multimedia content delivery, and data hiding for watermarking (for proving ownership). A robust watermarking protocol for unambiguous resolution of ownership is proposed

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

MP3 audio steganography technique using extended least significant bit

Audio Steganography is the process of concealing secret messages into audio file. The goal for using audio steganography is to avoid drawing suspicion to the transmission of the secret message. Prior research studies have indicated that the main properties in steganography technique are imperceptibility, robustness and capacity. MP3 file is a popular audio media, which provides different compression rate and performing steganography in MP3 format after compression is the most desirable one. To date, there is not much research work that embeds messages after compression. An audio steganographic technique that utilizes Standard Least Significant Bits (SLSB) of the audio stream to embed secret message has gained popularity over the years. Unfortunately the technique suffers from imperceptibility, security and capacity. This research offers an extended Least Significant Bit (XLSB) technique in order to circumvent the weakness. The secret message is scrambled before embedding. Scrambling technique is introduced in two steps; partitioning the secret message (speech) into blocks followed by block permutation, in order to confuse the contents of the secret message. To enhance difficulty for attackers to retrieve the secret message, the message is not embedded in every byte of the audio file. Instead the first position of embedding bit is chosen randomly and the rest of the bits are embedded only in even value of bytes of the audio file. For extracting the secret message, the permutation code book is used to reorder the message blocks into its original form. Md5sum and SHA-256 are used to verify whether the secret message is altered or not during transmission. Experimental results measured by peak signal to noise ratio, bit error rate, Pearson Correlation and chi-square show that the XLSB performs better than SLSB. Moreover, XLSB can embed a maximum of 750KB into MP3 file with 30db average result. This research contributes to the information security community by providing more secure steganography technique which provides message confidentiality and integrity

Enhancement of digital grayscale image watermarking using sparse matrix

Watermarking is a form of steganography that proved its worth in successfully protecting copyright information. It is the process of embedding data inside an audio or video or image message such that the embedded data is possible to be detected or extracted later. The core focus in watermarking techniques is their performance which is determined by imperceptibility along with robustness and capacity. These properties are often conflicting, which needs to accept some trade-offs between them. Despite the successes recorder in the area of digital watermarking, several challenges continue to persist particularly in the Areas of balancing these factors. This research aims to enhance the the processes in the watermarking technique for archieving imperceptibility with an acceptable balancing and enhance the security. The research proposed a new scheme using sparse matrix for improving the effectiveness of watermarked image using digital wavelet transform and inverse discrete wavelet transform to locate the best place and level in the image to embed the watermark. Sparse matrix is used to enhance the embedding process by selecting the proper coefficient. For more secure watermarking, additional encryption layer is utilized to increase the difficulty towards unauthorized extraction. The proposed technique generated the proper message size for each sub image based on the PSNR, which is used as an indicator for selecting the suitable level of embedding and for detecting the possibility of attacks. The proposed scheme improves watermarking quality by using the sparse matrix to select the appropriate coefficient for embedding. The experiments showed that the proposed scheme enhances 2.8479 dB of quality (PSNR) or equivalent to 5.3 % of improvements. The research proposed scheme achieved better PSNR in comparison with other research

Data Hiding in Digital Video

With the rapid development of digital multimedia technologies, an old method which is called steganography has been sought to be a solution for data hiding applications such as digital watermarking and covert communication. Steganography is the art of secret communication using a cover signal, e.g., video, audio, image etc., whereas the counter-technique, detecting the existence of such as a channel through a statistically trained classifier, is called steganalysis. The state-of-the art data hiding algorithms utilize features; such as Discrete Cosine Transform (DCT) coefficients, pixel values, motion vectors etc., of the cover signal to convey the message to the receiver side. The goal of embedding algorithm is to maximize the number of bits sent to the decoder side (embedding capacity) with maximum robustness against attacks while keeping the perceptual and statistical distortions (security) low. Data Hiding schemes are characterized by these three conflicting requirements: security against steganalysis, robustness against channel associated and/or intentional distortions, and the capacity in terms of the embedded payload. Depending upon the application it is the designer\u27s task to find an optimum solution amongst them. The goal of this thesis is to develop a novel data hiding scheme to establish a covert channel satisfying statistical and perceptual invisibility with moderate rate capacity and robustness to combat steganalysis based detection. The idea behind the proposed method is the alteration of Video Object (VO) trajectory coordinates to convey the message to the receiver side by perturbing the centroid coordinates of the VO. Firstly, the VO is selected by the user and tracked through the frames by using a simple region based search strategy and morphological operations. After the trajectory coordinates are obtained, the perturbation of the coordinates implemented through the usage of a non-linear embedding function, such as a polar quantizer where both the magnitude and phase of the motion is used. However, the perturbations made to the motion magnitude and phase were kept small to preserve the semantic meaning of the object motion trajectory. The proposed method is well suited to the video sequences in which VOs have smooth motion trajectories. Examples of these types could be found in sports videos in which the ball is the focus of attention and exhibits various motion types, e.g., rolling on the ground, flying in the air, being possessed by a player, etc. Different sports video sequences have been tested by using the proposed method. Through the experimental results, it is shown that the proposed method achieved the goal of both statistical and perceptual invisibility with moderate rate embedding capacity under AWGN channel with varying noise variances. This achievement is important as the first step for both active and passive steganalysis is the detection of the existence of covert channel. This work has multiple contributions in the field of data hiding. Firstly, it is the first example of a data hiding method in which the trajectory of a VO is used. Secondly, this work has contributed towards improving steganographic security by providing new features: the coordinate location and semantic meaning of the object

High payload digital image steganography using mixed edge detection mechanism

The Least Significant Bit(LSB) is a spatial domain embedding technique suggest that data can be hidden in the least significant bits of the cover image and the human visual system(HVS) not able to find the secret data in the cover image. It is most powerful and easily understood method in spatial domain. LSB is widely used stegonagraphy technique in both spatial and frequency domain because all other methods in frequency domain are complex to understand and implement. In this thesis, along with using the LSB substitution method as a important stage, edge detection mechanism is used to take advantage for high payload, as edges are sharp areas of an image. In the proposed scheme, mixed edge detection mechanism is employed to achieve high payload steganography. Here, mixed edge detection mechanism is combination of Canny edge detection and Log edge detection techniques. Then applying the embedding algorithm, heavy amount data are stored in the cover image i.e high payload is achieved. Experimental results show that the steganography using mixed or hybrid edge detection mechanism accomplished with better peak signal to noise ratio(PSNR), compare to other steganograpgic model, for the same number of bits per pixel in embedded image