Study of Reversible Scheme for Data Hiding

Web is the prominent correspondence media now a days yet message exchange over the web is confronting a few issue, for example, copyright control, information security, information, confirmation and so forth. Information stowing away assumes a critical part in information security. It is a procedure in which mystery information or data is put away or covered up into cover media. Thus many explores are advancing on the field like web security, steganography, and cryptography. At the point when exchange the safe or private information over a shaky channel it is expected to encode cover or unique information and after that insert the protected information into that unique or, on the other hand cover picture

Improved Capacity Image Steganography Algorithm using 16-Pixel Differencing with n-bit LSB Substitution for RGB Images

With the intrusion of internet into the lives of every household and terabytes of data being transmitted over the internet on daily basis, the protection of content being transmitted over the internet has become an extremely serious concern. Various measures and methods are being researched and devised everyday to ensure content protection of digital media. To address this issue of content protection, this paper proposes an RGB image steganography based on sixteen-pixel differencing with n-bit Least Significant Bit (LSB) substitution. The proposed technique provides higher embedding capacity without sacrificing the imperceptibility of the host data. The image is divided into 4×4 non overlapping blocks and in each block the average difference value is calculated. Based on this value the block is classified to fall into one of four levels such as, lower, lower-middle, higher-middle and higher. If block belongs to lower level then 2-bit LSB substitution is used in it. Similarly, for lower-middle, higher-middle and higher level blocks 3, 4, and 5 bit LSB substitution is used. In our proposed method there is no need of pixel value readjustment for minimizing distortion. The experimental results show that stego-images are imperceptible and have huge hiding capacity

A review and open issues of multifarious image steganography techniques in spatial domain

Nowadays, information hiding is becoming a helpful technique and fetch more attention due fast growth of using internet, it is applied for sending secret information by using different techniques. Steganography is one of major important technique in information hiding. Steganography is science of concealing the secure information within a carrier object to provide the secure communication though the internet, so that no one can recognize and detect it’s except the sender & receiver. In steganography, many various carrier formats can be used such as an image, video, protocol, audio. The digital image is most popular used as a carrier file due its frequency on internet. There are many techniques variable for image steganography, each has own strong and weak points. In this study, we conducted a review of image steganography in spatial domain to explore the term image steganography by reviewing, collecting, synthesizing and analyze the challenges of different studies which related to this area published from 2014 to 2017. The aims of this review is provides an overview of image steganography and comparison between approved studies are discussed according to the pixel selection, payload capacity and embedding algorithm to open important research issues in the future works and obtain a robust method

Hiding Data in Image using Extended Pixel Mapping Method

— Internet technologies are currently charring an important role in our day to day life. It has the benefit as well as disadvantages also.This in term generates the needs of data activity technology for maintaining the secrecy of the key information. The steganograpic concept of data hiding is used in this method. The method used spatial domain technique. This algorithm used image as a carrier medium for hiding the data. In this pixel component are used for hiding the data. For achieving this pixel index value and their position are calculated. According to this key will be generated and by using key data is hided.Experimental result shows that the perceptual quality of hided image is high in this technique. The key idea of this project is to hide the data in carrier image and retrieve data from carrier image without affecting without affecting the perceptual transparency of the data hided image. This system provides compression of data so that payload capacity of the system will be increases. DOI: 10.17762/ijritcc2321-8169.150512

Comparative Analysis of Hybrid Algorithms in Information Hiding

In this present work, propose comparative algorithms to conceal information into the image using steganography method. The proposedalgorithms use binary codes and pixels inside an image. The zipped file is used before it is transformed to binary codes to make the most of the storage of data inside the image. By applying the algorithms, a system called Steganography Imaging Information System (SIIS) is developed. The system is then tested to see the viability of the proposed algorithm. Different sizes of data are stored inside the images and the PSNR (Peak signal-to-noise ratio) is also captured for each of the images tested. According to the PSNR value of each image, the concealed image has a higher PSNR value. Therefore, this new steganography algorithm efficiently hides the data in the image

A High Secured Steganalysis using QVDHC Model

Data compression plays a vital role in data security as it saves memory, transfer speed is high, easy to handle and secure. Mainly the compression techniques are categorized into two types. They are lossless, lossy data compression. The data format will be an audio, image, text or video. The main objective is to save memory of using these techniques is to save memory and to preserve data confidentiality, integrity. In this paper, a hybrid approach was proposed which combines Quotient Value Difference (QVD) with Huffman coding. These two methods are more efficient, simple to implement and provides better security to the data. The secret message is encoded using Huffman coding, while the cover image is compressed using QVD. Then the encoded data is embedded into cover image and transferred over the network to receiver. At the receiver end, the data is decompressed to obtain original message. The proposed method shows high level performance when compared to other existing methods with better quality and minimum error

Introducing a New Evaluation Criteria for EMD-Base Steganography Method

Steganography is a technique to hide the presence of secret communication. When one of the communication elements is under the influence of the enemy, it can be used. The main measure to evaluate steganography methods in a certain capacity is security. Therefore, in a certain capacity, reducing the amount of changes in the cover media, creates a higher embedding efficiency and thus more security of an steganography method. Mostly, security and capacity are in conflict with each other, the increase of one lead to the decrease of the other. The presence of a single criterion that represents security and capacity at the same time be useful in comparing steganography methods. EMD and the relevant methods are a group of steganography techniques, which optimize the amount of changes resulting from embedding (security). The present paper is aimed to provide an evaluation criterion for this group of steganography methods. In this study, after a general review and comparison of EMD-based steganography techniques, we present a method to compare them exactly, from the perspective of embedding efficiency. First, a formula is presented to determine the value of embedding efficiency, which indicates the effect of one or more changes on one or more pixels. The results demonstrate that the proposed embedding efficiency formula shows the performance of the methods better when several changes are made on a pixel compared to the existing criteria. In the second step, we have obtained an upper bound, which determines the best efficiency for each certain capacity. Finally, based on the introduced bound, another evaluation criterion for a better comparison of the methods is presented