Color image steganography in YCbCr space

Steganography is a best method for in secret communicating information during the transference of data. Images are an appropriate method that used in steganography can be used to protection the simple bits and pieces. Several systems, this one as color scale images steganography and grayscale images steganography, are used on color and store data in different techniques. These color images can have very big amounts of secret data, by using three main color modules. The different color modules, such as HSV-(hue, saturation, and value), RGB-(red, green, and blue), YCbCr-(luminance and chrominance), YUV, YIQ, etc. This paper uses unusual module to hide data: an adaptive procedure that can increase security ranks when hiding a top secret binary image in a RGB color image, which we implement the steganography in the YCbCr module space. We performed Exclusive-OR (XOR) procedures between the binary image and the RGB color image in the YCBCR module space. The converted byte stored in the 8-bit LSB is not the actual bytes; relatively, it is obtained by translation to another module space and applies the XOR procedure. This technique is practical to different groups of images. Moreover, we see that the adaptive technique ensures good results as the peak signal to noise ratio (PSNR) and stands for mean square error (MSE) are good. When the technique is compared with our previous works and other existing techniques, it is shown to be the best in both error and message capability. This technique is easy to model and simple to use and provides perfect security with unauthorized

An Efficient Video Steganography Algorithm Based on BCH Codes

© ASEE 2015In this paper, in order to improve the security and efficiency of the steganography algorithm, we propose an efficient video steganography algorithm based on the binary BCH codes. First the pixels’ positions of the video frames’ components are randomly permuted by using a private key. Moreover, the bits’ positions of the secret message are also permuted using the same private key. Then, the secret message is encoded by applying BCH codes (n, k, t), and XORed with random numbers before the embedding process in order to protect the message from being read. The selected embedding area in each Y, U, and V frame components is randomly chosen, and will differ from frame to frame. The embedding process is achieved by hiding each of the encoded blocks into the 3-2-2 least significant bit (LSB) of the selected YUV pixels. Experimental results have demonstrated that the proposed algorithm have a high embedding efficiency, high embedding payload, and resistant against hackers

A Highly Secure Video Steganography using Hamming Code (7, 4)

Due to the high speed of internet and advances in technology, people are becoming more worried about information being hacked by attackers. Recently, many algorithms of steganography and data hiding have been proposed. Steganography is a process of embedding the secret information inside the host medium (text, audio, image and video). Concurrently, many of the powerful steganographic analysis software programs have been provided to unauthorized users to retrieve the valuable secret information that was embedded in the carrier files. Some steganography algorithms can be easily detected by steganalytical detectors because of the lack of security and embedding efficiency. In this paper, we propose a secure video steganography algorithm based on the principle of linear block code. Nine uncompressed video sequences are used as cover data and a binary image logo as a secret message. The pixels’ positions of both cover videos and a secret message are randomly reordered by using a private key to improve the system’s security. Then the secret message is encoded by applying Hamming code (7, 4) before the embedding process to make the message even more secure. The result of the encoded message will be added to random generated values by using XOR function. After these steps that make the message secure enough, it will be ready to be embedded into the cover video frames. In addition, the embedding area in each frame is randomly selected and it will be different from other frames to improve the steganography scheme’s robustness. Furthermore, the algorithm has high embedding efficiency as demonstrated by the experimental results that we have obtained. Regarding the system’s quality, the Pick Signal to Noise Ratio (PSNR) of stego videos are above 51 dB, which is close to the original video quality. The embedding payload is also acceptable, where in each video frame we can embed 16 Kbits and it can go up to 90 Kbits without noticeable degrading of the stego video’s quality

A DWT-BCH code based Video Steganography by employing Variable bit length Algorithm

Due to the high speed of Internet we can easily transfer video data over the Internet, but people are worried about their data being hacked by unauthorized users. Inside the host medium (text, audio, image and video) we can embed the secret message in Steganography. Video Steganography is a significant method for data hiding. In this work, a variable bit length Video Steganography algorithm is proposed. To immune the secret data, it is first encoded using BCH codes, where the message bits of length k will be converted to a codeword of length n. Depending on the wavelet coefficient values of DWT(Discrete wavelet transform), secret data are embedded into the middle and high frequencies. The results demonstrate better results than in [1]

The Implementation of Hamming Code Using Video Steganography

As time goes on, the internet world grows larger and larger. The massive number of people involved in the internet means that there are more data flying around in cyberspace waiting for someone to receive it; that is where the need for steganography emerges. The role of steganography is to ensure that the necessary transmitted data does not fall in the hands of the wrong person. It hides the vital data inside an image or video without noticeable changes, where only a key provided by the sender allows the receiver to crack open the cover and see the original data. Steganography is often mistaken as a method of cryptography. In fact, they are two different methods, but they can be used together. In cryptography, the observer can detect that there is a hidden message but he doesn’t have the required tools to crack it. Hamming code is a type of cryptography and it’s use in my paper will strengthen the security of this implementation and make it even harder to decipher

Optimal Color Model for Information Hidingin Color Images

In present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images

A One-dimensional HEVC video steganalysis method using the Optimality of Predicted Motion Vectors

Among steganalysis techniques, detection against motion vector (MV) domain-based video steganography in High Efficiency Video Coding (HEVC) standard remains a hot and challenging issue. For the purpose of improving the detection performance, this paper proposes a steganalysis feature based on the optimality of predicted MVs with a dimension of one. Firstly, we point out that the motion vector prediction (MVP) of the prediction unit (PU) encoded using the Advanced Motion Vector Prediction (AMVP) technique satisfies the local optimality in the cover video. Secondly, we analyze that in HEVC video, message embedding either using MVP index or motion vector differences (MVD) may destroy the above optimality of MVP. And then, we define the optimal rate of MVP in HEVC video as a steganalysis feature. Finally, we conduct steganalysis detection experiments on two general datasets for three popular steganography methods and compare the performance with four state-of-the-art steganalysis methods. The experimental results show that the proposed optimal rate of MVP for all cover videos is 100\%, while the optimal rate of MVP for all stego videos is less than 100\%. Therefore, the proposed steganography scheme can accurately distinguish between cover videos and stego videos, and it is efficiently applied to practical scenarios with no model training and low computational complexity.Comment: Submitted to TCSV

Hybrid Method For Image Watermarking Using 2 Level LWT-Walsh Transform-SVD in YCbCr Color Space

Due to tremendous development in technology in recent time and availability of abundant tool, it is very easy for an unauthorized person to imitate crucial information which is present on internet. Therefore to shield valuable information present on internet there are various advanced techniques for example watermarking technique, cryptography technique, steganography and many more. With pace of time analog techniques replaced by digital techniques due to various advantages and in current scenario every country moving towards digitalization. Digital watermarking is a technique through which digital information is embedded into an image and secret digital data can be extracted at receiver side with authentication otherwise impossible to fetch. Spatial domain and frequency are the two techniques through which secret digital information can be embedded. In this paper two level lifting wavelet transform (LWT), Walsh Hadamard transform and singular value decomposition (SVD) technique has been proposed in YCbCr color space. First of all cover image and watermark image converted into YCbCr color space from RGB color space after that one of channel is selected for embedded purpose. Now perform first level LWT on the Y channel of cover and watermark image so that image split into four groups. Now apply second level LWT on any one of four bands. Further Walsh hadamard transform technique applied with singular value decomposition (SVD) technique to get enhanced output. In base paper DWT-DFT-SVD used but in this paper DWT-DFT replaced by LWT-WHT due to various advantages. One disadvantage of DWT is that the use of larger DWT basis functions or wavelet filters produces blurring and also ringing noise near edges in images. This disadvantage of DWT is overcome in LWT. Other advantages of LWT are that it significantly reduces the computation time and speed up the computation process. This method provides better results in terms of enhanced PSNR values and is able to withstand a variety of image processing attacks and besides this processing time also reduced