Sharif Digital Repository

This study introduces a new scheme for steganalysis of the least significant bit (LSB) embedding, based on the idea of closure of sets (CoS), which is independent of the type of cover signal, applicable to both spatial and transform domains. The CoS is referred to as some special subsets that could be found in a common space whose elements relate to higher-order statistical properties of the signal. The proposed scheme is used for steganalysis of the LSB steganography of greyscale TIFF and JPEG images and audio signals, employing a set of accurate and monotone features that are extracted based on the CoS definition. It is shown that significant improvement to the detection accuracy in... 

Although phase change memory with multi-bit storage capability (known as MLC PCM) offers a good combination of high bit-density and non-volatility, its performance is severely impacted by the increased read/write latency. Regarding read operation, access latency increases almost linearly with respect to cell density (the number of bits stored in a cell). Since reads are latency critical, they can seriously impact system performance. This paper alleviates the problem of slow reads in the MLC PCM by exploiting a fundamental property of MLC devices: the Most-Significant Bit (MSB) of MLC cells can be read as fast as SLC cells, while reading the Least-Significant Bits (LSBs) is slower. We propose... 

In this paper, a novel steganographic method is proposed which is based on the spatial domain: Least Significant Bit (LSB). The LSB matching method proposed by Mielikainen utilizes a binary function to reduce the number of changed pixel values. While in this paper a bipolar evaluating system is proposed to assess the performance of different orders for LSB matching. Afterward a genetic algorithm strategy is employed to search for an optimal solution among all the permutation orders. The experimental results show that by employing the proposed bipolar evaluating system, the distortion of the stego-image is reduced while the probability of detection is decreased  

Steganalysis of least significant bit (LSB) embedded images in spatial domain has been investigated extensively over the past decade and most well-known LSB steganography methods have been shown to be detectable. However, according to the latest findings in the area, two major issues of very low-rate (VLR) embedding and content-adaptive steganography have remained hard to resolve. The problem of VLR embedding is indeed a generic problem to any steganalyser, while the issue of adaptive embedding specifically depends on the hiding algorithm employed. The latter challenge has recently been brought up again to the area of LSB steganalysis by highly undetectable stego image steganography that... 

A 1.8V, 10-Bit, 40-MS/s Pipeline analog-to-digital converter designed using 0.18-μmCMOS technology is presented. The new structure of the A/D converter is based on double sampling and averaging techniques. By the first technique, all the stage amplifiers are active at the both sampling and holding cycles. Averaging as the second technique minimizes the capacitance mismatch and exchanges the priority of input-referred noise and capacitance mismatch in the selection of the stage caps. The converter achieved a peak spurious-free- dynamic-range of 61 dB, maximum differential nonlinearity 0.5 of least significant bit (LSB), maximum integral linearity of 0.9 LSB, and power consumption of 5mW.... 

The Least Significant Bit (LSB) substitution is an old and simple data hiding method that could almost effortlessly be implemented in spatial or transform domain over any digital media. This method can be attacked by several steganalysis methods, because it detectably changes statistical and perceptual characteristics of the cover signal. A typical method for steganalysis of the LSB substitution is the histogram attack that attempts to diagnose anomalies in the cover image's histogram. A well-known method to stand the histogram attack is the LSB + steganography that intentionally embeds some extra bits to make the histogram look natural. However, the LSB + method still affects the perceptual... 

A highly energy-efficiency switching procedure for the capacitor-splitting digital-To-Analog converter (DAC) is presented for successive approximation register (SAR) analogue-To-digital converters (ADCs). In this procedure, the MSB capacitor is divided into its binary constituents. All output digital bits, except the least significant bit (LSB), is determined using reference voltage (Vref), while the common-mode voltage (Vcm) is used to determine the LSB. Therefore, the precision of the proposed SAR ADC is independent of the precision of Vcm except in the LSB. This method reduces the area by 75% compared to the conventional binary weighted DAC and reduces the switching energy by 96.89%. ©... 

This paper introduces a new method for the least significant bit (LSB) steganography in spatial domain. The new method, called one-third LSB embedding, reduces the probability of change per pixel to one-third without sacrificing the embedding capacity, as compared to previous LSB steganography techniques. This improvement results in a better imperceptibility and higher robustness against well known LSB detectors. Each bit of the message is carried through a function of three adjacent cover pixels and it is shown that no significant improvement is achieved by increasing the length of the pixel sequence employed. ©2009 IEEE  

This paper introduces a novel method to detect the typical LSB (Least Significant Bit) embedding and the LSB matching steganography methods applied to grayscale images. The proposed method determines the changes made to some selected features extracted from the gray level run length matrix. It is shown that the run length characteristics can significantly be affected by the embedded message bits, so can be employed as a measure that is quite sensitive to the arrangements of the image pixel values. The extracted features are examined by a nonlinear SVM (Support Vector Machine) classifier with quadratic kernel that can distinguish between stego and clean images. Experimental results are given...