60 research outputs found

    A Review on Edge Based Image Steganography

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    Security of the information has always been the interesting area for researchers. Integrity, Confidentiality, and Authentication are main security principles. There are so many techniques developed to achieve these security principles using cryptography. But all these techniques are unable to keep the communication secret. Although the attacker is unable to access the secret message but he knows about the existence of the message. To overcome this limitation of cryptography a new idea is proposed by researchers that is Steganography. Steganography is the art of concealing secret message in a carrier such as text, image, audio, video and protocol messages. Different Steganography techniques are used based on these carrier messages and way of hiding. The choice of these method is depends on the requirements of application. Some application requires huge data embedding and some require high secrecy. This paper gives a review on image Steganography based on edge detection and their comparative study. It also gives an overview of basic edge detection techniques

    Detection of Motion Vector-Based Video Steganography by Adding or Subtracting One Motion Vector Value

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    In last decades the Steganography is an tremendous progress, at the same time there exist issues to detect the steganalysis in motion based video where the substance is reliably in motion conduct that makes that to detect it. Analyzing the difference between the rated motion value plays a crucial role that enables us to focus on difference between the locally optimal SAD and actual SAD after adding-or-subtracting-one operation on the motion value. Based on the motion vectors to play out the classification and extraction process at last, two features sets are been used based on the fact that most motion vectors are locally optimal for most video codec’s to complete this process. The conventional approaches announced the technique for proposed prevails to meet the requirement applications and detecting the steganalysis in videos compare in the literature

    Edge-based image steganography

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    A Study of Data Security on E-Governance using Steganographic Optimization Algorithms

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    Steganography has been used massively in numerous fields to maintain the privacy and integrity of messages transferred via the internet. The need to secure the information has augmented with the increase in e-governance usage. The wide adoption of e-governance services also opens the doors to cybercriminals for fraudulent activities in cyberspace. To deal with these cybercrimes we need optimized and advanced steganographic techniques. Various advanced optimization techniques can be applied to steganography to obtain better results for the security of information. Various optimization techniques like particle swarm optimization and genetic algorithms with cryptography can be used to protect information for e-governance services. In this study, a comprehensive review of steganographic algorithms using optimization techniques is presented. A new perspective on using this technique to protect the information for e-governance is also presented. Deep Learning might be the area that can be used to automate the steganography process in combination with other method

    Detecting covert communication channels in raster images

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    Digital image steganography is a method for hiding secret messages within everyday Internet communication channels. Such covert communications provide protection for communications and exploit the opportunities available in digital media. Digital image steganography makes the nature and content of a message invisible to other users by taking ordinary internet artefacts and using them as cover objects for the messages. In this paper we demonstrate the capability with raster image files and discuss the challenges of detecting such covert communications. The contribution of the research is community awareness of covert communication capability in digital media and the motivation for including such checks in any investigatory analysis

    Data hiding techniques in steganography using fibonacci sequence and knight tour algorithm

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    The foremost priority in the information and communication technology era, is achieving an efficient and accurate steganography system for hiding information. The developed system of hiding the secret message must capable of not giving any clue to the adversaries about the hidden data. In this regard, enhancing the security and capacity by maintaining the Peak Signal-to-Noise Ratio (PSNR) of the steganography system is the main issue to be addressed. This study proposed an improved for embedding secret message into an image. This newly developed method is demonstrated to increase the security and capacity to resolve the existing problems. A binary text image is used to represent the secret message instead of normal text. Three stages implementations are used to select the pixel before random embedding to select block of (64 Ă— 64) pixels, follows by the Knight Tour algorithm to select sub-block of (8 Ă— 8) pixels, and finally by the random pixels selection. For secret embedding, Fibonacci sequence is implemented to decomposition pixel from 8 bitplane to 12 bitplane. The proposed method is distributed over the entire image to maintain high level of security against any kind of attack. Gray images from the standard dataset (USC-SIPI) including Lena, Peppers, Baboon, and Cameraman are implemented for benchmarking. The results show good PSNR value with high capacity and these findings verified the worthiness of the proposed method. High complexities of pixels distribution and replacement of bits will ensure better security and robust imperceptibility compared to the existing systems in the literature

    A New Optimization Strategy for Solving the Fall-Off Boundary Value Problem in Pixel-Value Di®erencing Steganography

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    In Digital Image Steganography, Pixel-Value Di®erencing (PVD) methods use the di®erence between neighboring pixel values to determine the amount of data bits to be inserted. The main advantage of these methods is the size of input data that an image can hold. However, the fall- o® boundary problem and the fall in error problem are persistent in many PVD steganographic methods. This results in an incorrect output image. To ¯x these issues, usually the pixel values are either somehow adjusted or simply not considered to carry part of the input data. In this paper, we enhance the Tri-way Pixel-Value Di®erencing method by ¯nding an optimal pixel value for each pixel pair such that it carries the maximum input data possible without ignoring any pair and without yielding incorrect pixel values

    An improved image steganography scheme based on distinction grade value and secret message encryption

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    Steganography is an emerging and greatly demanding technique for secure information communication over the internet using a secret cover object. It can be used for a wide range of applications such as safe circulation of secret data in intelligence, industry, health care, habitat, online voting, mobile banking and military. Commonly, digital images are used as covers for the steganography owing to their redundancy in the representation, making them hidden to the intruders, hackers, adversaries, unauthorized users. Still, any steganography system launched over the Internet can be cracked upon recognizing the stego cover. Thus, the undetectability that involves data imperceptibility or concealment and security is the significant trait of any steganography system. Presently, the design and development of an effective image steganography system are facing several challenges including low capacity, poor robustness and imperceptibility. To surmount such limitations, it is important to improve the capacity and security of the steganography system while maintaining a high signal-to-noise ratio (PSNR). Based on these factors, this study is aimed to design and develop a distinction grade value (DGV) method to effectively embed the secret data into a cover image for achieving a robust steganography scheme. The design and implementation of the proposed scheme involved three phases. First, a new encryption method called the shuffle the segments of secret message (SSSM) was incorporated with an enhanced Huffman compression algorithm to improve the text security and payload capacity of the scheme. Second, the Fibonacci-based image transformation decomposition method was used to extend the pixel's bit from 8 to 12 for improving the robustness of the scheme. Third, an improved embedding method was utilized by integrating a random block/pixel selection with the DGV and implicit secret key generation for enhancing the imperceptibility of the scheme. The performance of the proposed scheme was assessed experimentally to determine the imperceptibility, security, robustness and capacity. The standard USC-SIPI images dataset were used as the benchmarking for the performance evaluation and comparison of the proposed scheme with the previous works. The resistance of the proposed scheme was tested against the statistical, X2 , Histogram and non-structural steganalysis detection attacks. The obtained PSNR values revealed the accomplishment of higher imperceptibility and security by the proposed DGV scheme while a higher capacity compared to previous works. In short, the proposed steganography scheme outperformed the commercially available data hiding schemes, thereby resolved the existing issues
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