276 research outputs found

    Unified Description for Network Information Hiding Methods

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    Until now hiding methods in network steganography have been described in arbitrary ways, making them difficult to compare. For instance, some publications describe classical channel characteristics, such as robustness and bandwidth, while others describe the embedding of hidden information. We introduce the first unified description of hiding methods in network steganography. Our description method is based on a comprehensive analysis of the existing publications in the domain. When our description method is applied by the research community, future publications will be easier to categorize, compare and extend. Our method can also serve as a basis to evaluate the novelty of hiding methods proposed in the future.Comment: 24 pages, 7 figures, 1 table; currently under revie

    Comparative Analysis of Hybrid Algorithms in Information Hiding

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    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

    Reversible Embedding to Covers Full of Boundaries

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    In reversible data embedding, to avoid overflow and underflow problem, before data embedding, boundary pixels are recorded as side information, which may be losslessly compressed. The existing algorithms often assume that a natural image has little boundary pixels so that the size of side information is small. Accordingly, a relatively high pure payload could be achieved. However, there actually may exist a lot of boundary pixels in a natural image, implying that, the size of side information could be very large. Therefore, when to directly use the existing algorithms, the pure embedding capacity may be not sufficient. In order to address this problem, in this paper, we present a new and efficient framework to reversible data embedding in images that have lots of boundary pixels. The core idea is to losslessly preprocess boundary pixels so that it can significantly reduce the side information. Experimental results have shown the superiority and applicability of our work

    An Analysis of Perturbed Quantization Steganography in the Spatial Domain

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    Steganography is a form of secret communication in which a message is hidden into a harmless cover object, concealing the actual existence of the message. Due to the potential abuse by criminals and terrorists, much research has also gone into the field of steganalysis - the art of detecting and deciphering a hidden message. As many novel steganographic hiding algorithms become publicly known, researchers exploit these methods by finding statistical irregularities between clean digital images and images containing hidden data. This creates an on-going race between the two fields and requires constant countermeasures on the part of steganographers in order to maintain truly covert communication. This research effort extends upon previous work in perturbed quantization (PQ) steganography by examining its applicability to the spatial domain. Several different information-reducing transformations are implemented along with the PQ system to study their effect on the security of the system as well as their effect on the steganographic capacity of the system. Additionally, a new statistical attack is formulated for detecting ± 1 embedding techniques in color images. Results from performing state-of-the-art steganalysis reveal that the system is less detectable than comparable hiding methods. Grayscale images embedded with message payloads of 0.4bpp are detected only 9% more accurately than by random guessing, and color images embedded with payloads of 0.2bpp are successfully detected only 6% more reliably than by random guessing

    Steganography Approach to Image Authentication Using Pulse Coupled Neural Network

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    This paper introduces a model for the authentication of large-scale images. The crucial element of the proposed model is the optimized Pulse Coupled Neural Network. This neural network generates position matrices based on which the embedding of authentication data into cover images is applied. Emphasis is placed on the minimalization of the stego image entropy change. Stego image entropy is consequently compared with the reference entropy of the cover image. The security of the suggested solution is granted by the neural network weights initialized with a steganographic key and by the encryption of accompanying steganographic data using the AES-256 algorithm. The integrity of the images is verified through the SHA-256 hash function. The integration of the accompanying and authentication data directly into the stego image and the authentication of the large images are the main contributions of the work

    SYNTEZA OPTYMALNEJ METODY STEGANOGRAFII WEDŁUG WYBRANYCH KRYTERIÓW

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    One of the steganography areas is digital watermarking. In this paper, the technique of comparative analysis of embedding information methods into an image was proposed. A comprehensive analysis of the most relevant steganographic methods of hiding information was made. Own method of embedding information in still images was synthesized. The possibility of studied methods to adapt to the real channels was evaluated for the first time. The robustness and security of steganographic systems based on the proposed method were also demonstrated.Jednym z obszarów steganografii jest osadzanie cyfrowych znaków wodnych. W niniejszej pracy zaproponowano metodykę analizy porównawczej metod osadzania informacji w obrazach. Została dokonana wszechstronna analiza najnowszych metod ukrywania informacji za pomocą steganografii. Opracowano własną metodę osadzania informacji w nieruchomych obrazach. Oceniono możliwość adaptowania się metod do charakterystyk rzeczywistych kanałów komunikacyjnych. Wykazano wiarygodność i bezpieczeństwo systemów steganograficznych wykorzystujących proponowaną metodę

    Enhanced Stegano-Cryptographic Model for Secure Electronic Voting

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    The issue of security in Information and Communication Technology has been identified as the most critical barrier in the widespread adoption of electronic voting (e-voting). Earlier cryptographic models for secure e-voting are vulnerable to attacks and existing stegano-cryptographic models can be manipulated by an eavesdropper. These shortcomings of existing models of secure e-voting are threats to confidentiality, integrity and verifiability of electronic ballot which are critical to overall success of e-democratic decision making through e-voting.This paper develops an enhanced stegano-cryptographic model for secure electronic voting system in poll-site, web and mobile voting scenarios for better citizens’ participation and credible e-democratic election. The electronic ballot was encrypted using Elliptic Curve Cryptography and Rivest-Sharma-Adleman cryptographic algorithm. The encrypted voter’s ballot was scattered and hidden in the Least Significant Bit (LSB) of the cover media using information hiding attribute of modified LSB-Wavelet steganographic algorithm. The image quality of the model, stego object was quantitatively assessed using Peak Signal to Noise Ratio (PSNR), Signal to Noise Ratio (SNR), Root Mean Square Error (RMSE) and Structural Similarity Index Metrics (SSIM).The results after quantitative performance evaluation shows that the developed stegano-cryptographic model has generic attribute of secured e-voting relevant for the delivery of credible e-democratic decision making. The large scale implementation of the model would be useful to deliver e-voting of high electoral integrity and political trustworthiness, where genuine e-elections are conducted for the populace by government authority. Keywords: Electronic Voting, Cryptography, Steganography, Video, Image, Wavelet, Securit

    Data Hiding Based on Intelligent Optimized Edges for Secure Multimedia Communication

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    Recently, image steganography has received a lot of attention as it enables for secure multimedia communication. Payload capacity and stego image imperceptibility are a critical factors of any steganographic technique. In order to receive maximum embedding capacity with a minimum degradation of stego images, secret data should be embedded carefully in a specific regions. In this paper, data hiding is considered as an optimization problem related to achieving optimum embedding level of the cover image. Embedding data in edge area provide high imperceptibility. However, the embedding capacity of edge region is very limited. The work attempt to improve the edge based steganography by incorporates edge detection and vision science research. Genetic Algorithm that uses human visual system characteristics approach for data hiding is presented. Primarily, the approach applies Differences of Gaussian detector which closely resembles the human visual behavior. Secondly, the edge profusion indicates the level of threshold visibility with the help of Genetic Algorithm training. The suggested solution uses Contrast Sensitivity Function (CSF) which produces the edges based on the size of the embedding information. The authors of this paper compared their technique with other classical and recent works. The quality of the steganography is measured based on various quality metrics such as PSNR, wPSNR, SSIM and UIQI. These metrics declare the stability between imperceptibility and large embedding capacit
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