Biblio

Edge detection based embedding techniques are famous for data security and image quality preservation. These techniques use diverse edge detectors to classify edge and non-edge pixels in an image and then implant secrets in one or both of these classes. Image with conceived data is called stego image. It is noticeable that none of such researches tries to reform the original image from the stego one. Rather, they devote their concentration to extract the hidden message only. This research presents a solution to the raised reversibility problem. Like the others, our research, first, applies an edge detector e.g., canny, in a cover image. The scheme next collects \$n\$-LSBs of each of edge pixels and finally, concatenates them with encrypted message stream. This method applies a lossless compression algorithm to that processed stream. Compression factor is taken such a way that the length of compressed stream does not exceed the length of collected LSBs. The compressed message stream is then implanted only in the edge pixels by \$n\$-LSB substitution method. As the scheme does not destroy the originality of non-edge pixels, it presents better stego quality. By incorporation the mechanisms of encryption, concatenation, compression and \$n\$-LSB, the method has enriched the security of implanted data. The research shows its effectiveness while implanting a small sized message.

Cryptography is a powerful means of delivering information in a secure manner. Over the years, many image encryption algorithms have been proposed based on the chaotic system to protect the digital image against cryptography attacks. In chaotic encryption, it jumbles the image to vary the framework of the image. This makes it difficult for the attacker to retrieve the original image. This paper introduces an efficient image encryption algorithm incorporating the genetic algorithm, bit plane slicing and bit plane rotation of the digital image. The digital image is sliced into eight planes and each plane is well rotated to give a fully encrypted image after the application of the Genetic Algorithm on each pixel of the image. This makes it less prone to attacks. For decryption, we perform the operations in the reverse order. The performance of this algorithm is measured using various similarity measures like Structural Similarity Index Measure (SSIM). The results exhibit that the proposed scheme provides a stronger level of encryption and an enhanced security level.

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.

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.

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).