Implementation of image steganography algorithm using scrambled image and quantization coefficient modification in DCT

Abstract: Rapid development of Internet makes transactions message even easier and faster. The main problem in the transactions message is security, especially if the message is private and secret. To secure these messages is usually done with steganography or cryptography. Steganography is a way to hide messages into other digital content such as images, video or audio so it does not seem nondescript from the outside. While cryptography is a technique to encrypt messages so that messages can not be read directly. In this paper have proposed combination of steganography using discrete cosine transform (DCT) and cryptography using the one-time pad or vernam cipher implemented on a digital image. The measurement method used to determine the quality of stego image is the peak signal to noise ratio (PSNR) and ormalize cross Correlation (NCC) to measure the quality of the extraction of the decrypted message. Of steganography and encryption methods proposed obtained satisfactory results with PSNR and NCC high and resistant to JPEG compression and median filter. Keywords —Image Steganography, Discrete Cosine Transform (DCT), One Time Pad, Vernam, Chiper, Image Cryptography

Abstract: The security of sending confidential data on the internet is very important. Thus, the data security techniques must be developed. Techniques like cryptography and steganography are techniques that are widely used to protect information messages that are confidential. Steganography is a technique to hide, while cryptography is a technique to encode. The combination of the two techniques produces a better security system. This paper proposed a combination of steganography and cryptography by using Discrete Cosine Transform (DCT), One Time Pad (OTP) and PN-Sequence implemented on a digital image. The test and measurement method used to determine the quality of stego image or final image is using Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE). On the other hand, Normalized Correlation Coefficient (NCC) is used to measure the quality of extraction and decryption messages from the proposed StegoCrypt method. The experimental results of this study get better results compared to previous studies where this technique has better imperceptibility and is more resistant to JPEG compression, median filter, and crop attacks.

Abstract: Technology advances and easy access to multimedia tools with digital content have increased the number of issues in copyright procedures Digital watermarks are a set of techniques that are used to protect the copyright of digital content In this paper, a robust watermarking framework to embed a color watermark is presented To perform a color image as watermark, a method based on Discrete Cosine Transform (DCT) and Quantization Index Modulation (QIM) has been designed, besides, the color watermark is encoded in such a way that data to represent the colors are reduced Additionally, the coded watermark is embedded into the mid-frequency coefficients of DCT to ensure the robustness and imperceptibility of the watermark The efficiency of the proposed scheme against the most common attacks such as JPEG compression, impulsive and Gaussian noises, scaling, etc, has been tested in terms of Peak Signal-to-Noise Ratio (PSNR), Similarity Structural Index Measure (SSIM) and Normalized Correlation Coefficient (NCC) demonstrating good performance

Abstract: In this paper, a novel parallel color image watermarking scheme in the frequency domain for copyright protection of Multiple Picture Object (MPO) based on multithreading coding is proposed. Designed technique consists of three steps: firstly, the color watermark is codified using the Curvelet Transform (CvT), reducing quantity of information that represents the watermark; the second step represents the embedding process of a color watermark. In the embedding process, theMPO file contains two images where each image is divided in 8x8 pixels blocks applying DCT to any block. A color watermark is inserted in the medium frequency sub-bands of each DCT block, because the modifications performed in this sub-band are less perceptible by Human Visual System (HVS). Finally, during third step, the recovering process for color watermark is performed. The proposed scheme appears to demonstrate significant improvement in processing time though possible parallelization process when moving from serial programming to the use of threads in multicore CPUs. According to numerous experiments, where the Peak Signal-to-Noise Ratio (PSNR) and Similarity Structural Index Measure (SSIM) were used as quality criteria for watermarked MPO image and the recovered color watermark, novel method is not intrusive, since it does not degrade the quality of the watermarked MPO image. Additionally, the proposed framework is resistant to the most common image processing attacks.

Abstract: Cryptography and Steganography are two prominent techniques to obtain secure communication over the shared media like the Internet. Steganography is slightly ahead of cryptography because of its stealthy characteristics. In this paper, a new method has been proposed which combines cryptography and steganography to ensure even more secure communication. The Advanced Encryption Standard (AES) in spatial domain of the carrier/cover image and Least Significant Bit (LSB) replacement in the transformed domain of the same image has been used after performing a Discrete Cosine Transform (DCT) on the pixels. An additional layer of security has been introduced by applying XOR operation on the AES encrypted message with the pixel values of the carrier image. The Peak Signal to Noise Ratio (PSNR) of the proposed algorithm is better than most of the similar algorithms. With better PSNR, the proposed method depicts a three layer of security of the information and error free decryption.

Abstract: Objective methods for assessing perceptual image quality traditionally attempted to quantify the visibility of errors (differences) between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly adapted for extracting structural information from a scene, we introduce an alternative complementary framework for quality assessment based on the degradation of structural information. As a specific example of this concept, we develop a structural similarity index and demonstrate its promise through a set of intuitive examples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000. A MATLAB implementation of the proposed algorithm is available online at http://www.cns.nyu.edu//spl sim/lcv/ssim/.

Abstract: The discrete cosine transform (DCT) is a technique for converting a signal into elementary frequency components. It is widely used in image compression. Here we develop some simple functions to compute the DCT and to compress images. These functions illustrate the power of Mathematica in the prototyping of image processing algorithms. The rapid growth of digital imaging applications, including desktop publishing, multimedia, teleconferencing, and high-definition television (HDTV) has increased the need for effective and standardized image compression techniques. Among the emerging standards are JPEG, for compression of still images [Wallace 1991]; MPEG, for compression of motion video [Puri 1992]; and CCITT H.261 (also known as Px64), for compression of video telephony and teleconferencing. All three of these standards employ a basic technique known as the discrete cosine transform (DCT). Developed by Ahmed, Natarajan, and Rao [1974], the DCT is a close relative of the discrete Fourier transform (DFT). Its application to image compression was pioneered by Chen and Pratt [1984]. In this article, I will develop some simple functions to compute the DCT and show how it is used for image compression. We have used these functions in our laboratory to explore methods of optimizing image compression for the human viewer, using information about the human visual system [Watson 1993]. The goal of this paper is to illustrate the use of Mathematica in image processing and to provide the reader with the basic tools for further exploration of this subject.

Abstract: This paper presents analysis of Least Significant Bit (LSB) based Steganography and Discrete Cosine Transform (DCT) based Steganography. LSB based Steganography embed the text message in least significant bits of digital picture. Least significant bit (LSB) insertion is a common, simple approach to embedding information in a cover file. Unfortunately, it is vulnerable to even a small image manipulation. Converting an image from a format like GIF or BMP, which reconstructs the original message exactly (lossless compression) to a JPEG, which does not (lossy compression), and then back could destroy the information hidden in the LSBs. DCT based Steganography embed the text message in least significant bits of the Discrete Cosine (DC) coefficient of digital picture. When information is hidden inside video, the program hiding the information usually performs the DCT. DCT works by slightly changing each of the images in the video, only to the extent that is not noticeable by the human eye. An implementation of both these methods and their performance analysis has been done in this paper.

Abstract: Image steganography is the art of hiding information into a cover image. This paper presents a novel technique for Image steganography based on DWT, where DWT is used to transform original image (cover image) from spatial domain to frequency domain. Firstly two dimensional Discrete Wavelet Transform (2-D DWT) is performed on a gray level cover image of size M × N and Huffman encoding is performed on the secret messages/image before embedding. Then each bit of Huffman code of secret message/image is embedded in the high frequency coefficients resulted from Discrete Wavelet Transform. Image quality is to be improved by preserving the wavelet coefficients in the low frequency subband. The experimental results show that the algorithm has a high capacity and a good invisibility. Moreover PSNR of cover image with stego-image shows the better results in comparison with other existing steganography approaches. Furthermore, satisfactory security is maintained since the secret message/image cannot be extracted without knowing decoding rules and Huffman table.

Abstract: Steganography, the secret image is embedded in the cover image and transmitted in such a way that the existence of information is undetectable. The digital images, videos, sound files and other computer files can be used as carrier to embed the information. In this paper, we propose a modified secure and high capacity based steganography scheme of hiding a large-size secret image into a small-size cover image. Arnold transformation is performed to scrambles the secret image. Discrete Wavelet Transform (DWT) is performed in both images and followed by Alpha blending operation. Then the Inverse Discrete Wavelet Transformation (IDWT) is applied to get the stego image. We have investigated the performance of our scheme by comparing various qualities of the stego image and cover image. The results show that the proposed algorithm for modified steganography is highly secured with certain strength in addition to good perceptual invisibility.