Current Issue : April - June Volume : 2013 Issue Number : 2 Articles : 5 Articles
A novel data hiding scheme in digital images with the diamond encoding by pixel value adjustment is proposed. The proposed\r\nmethod is the extension of the exploiting modification direction (EMD) embedding scheme. First, the process of embedding\r\npartitions the cover image into nonoverlapping blocks of two consecutive pixels and transforms the secret messages to a series of\r\nk-ary digits. For each block, the diamond encoding technique is applied to calculate the diamond characteristic value, and one\r\nsecret k-ary digit is concealed into the diamond characteristic value. The diamond characteristic value is modified to secret digit\r\nand it can be obtained by adjusting pixel values in a block. This scheme is designed in such a way that the distortion of each block\r\nafter diamond encoding is never out of the embedding parameter k, and the block capacity is equal to log2(2k2 + 2k + 1). The\r\ndiamond encoding provides an easy way to produce a more perceptible result than those yielded by simple least-significant-bit\r\nsubstitution methods. The embedded secret data can be extracted without the original cover image. Experimental results have\r\ndemonstrated that the proposed method is capable of hiding more secret data while keeping the stego-image quality degradation\r\nimperceptible....
CardSpace (formerly known as InfoCard) is a digital identity management system that has recently been adopted by Microsoft. In\r\nthis paper we identify two security shortcomings in CardSpace that could lead to a serious privacy violation. The first is its reliance\r\non user judgements of the trustworthiness of service providers, and the second is its reliance on a single layer of authentication.\r\nWe also propose a modification designed to address both flaws. The proposed approach is compatible with the currently deployed\r\nCardSpace identity metasystem and should enhance the privacy of the system whilst involving only minor changes to the current\r\nCardSpace framework.We also provide a security and performance analysis of the proposal....
A novel model-based steganographic technique for JPEG images is proposed where the model, derived from heuristic assumptions\r\nabout the shape of the DCT frequency histograms, is dependent on a stegokey. The secret message is embedded in DCT domain\r\nthrough an accurate selection of the potentially modifiable coefficients, taking into account their visual and statistical relevancy.\r\nA novel block measure, named discrepancy, is introduced in order to select suitable areas for embedding. The visual impact of\r\nthe steganographic technique is evaluated through PSNR measures. State-of-the-art steganalytical test is also performed to offer a\r\ncomparison with the original model-based techniques....
This paper proposes to determine a sufficient number of images for reliable classification and to use feature selection to select most\r\nrelevant features for achieving reliable steganalysis. First dimensionality issues in the context of classification are outlined, and the\r\nimpact of the different parameters of a steganalysis scheme (the number of samples, the number of features, the steganography\r\nmethod, and the embedding rate) is studied. On one hand, it is shown that, using Bootstrap simulations, the standard deviation\r\nof the classification results can be very important if too small training sets are used; moreover a minimum of 5000 images is\r\nneeded in order to perform reliable steganalysis. On the other hand, we show how the feature selection process using the OP-ELM\r\nclassifier enables both to reduce the dimensionality of the data and to highlight weaknesses and advantages of the six most popular\r\nsteganographic algorithms....
A steganographic method called adjacent bin mapping (ABM) is presented. Firstly, it is applied to 3D geometries by mapping\r\nthe coordinates within two adjacent bins for data embedding. When applied to digital images, it becomes a kind of LSB hiding,\r\nnamely the LSB+ algorithm. In order to prevent the detection using a metric named histogram tail, the hiding is performed in a\r\npseudorandom order. Then we show that the steganalytic algorithms based on histogram characteristic function (HCF) can be\r\nprevented by implementing the LSB+ algorithm on subsets of pixels having the same neighbor values. The experimental results\r\nshow that important high-order statistics of the cover image are preserved in this way while little distortion is introduced to 3D\r\ngeometric models with an appropriate bin size...
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