Deep Convolutional Neural Network to Detect J-UNIWARD

This paper presents an empirical study on applying convolutional neural networks (CNNs) to detecting J-UNIWARD, one of the most secure JPEG steganographic method. Experiments guiding the architectural design of the CNNs have been conducted on the JPEG compressed BOSSBase containing 10,000 covers of size 512x512. Results have verified that both the pooling method and the depth of the CNNs are critical for performance. Results have also proved that a 20-layer CNN, in general, outperforms the most sophisticated feature-based methods, but its advantage gradually diminishes on hard-to-detect cases. To show that the performance generalizes to large-scale databases and to different cover sizes, one experiment has been conducted on the CLS-LOC dataset of ImageNet containing more than one million covers cropped to unified size of 256x256. The proposed 20-layer CNN has cut the error achieved by a CNN recently proposed for large-scale JPEG steganalysis by 35%. Source code is available via GitHub: https://github.com/GuanshuoXu/deep_cnn_jpeg_steganalysisComment: Accepted by IH&MMSec 2017. This is a personal cop

Is ensemble classifier needed for steganalysis in high-dimensional feature spaces?

International audienceThe ensemble classifier, based on Fisher Linear Discriminant base learners, was introduced specifically for steganalysis of digital media, which currently uses high-dimensional feature spaces. Presently it is probably the most used method to design supervised classifier for steganalysis of digital images because of its good detection accuracy and small computational cost. It has been assumed by the community that the classifier implements a non-linear boundary through pooling binary decision of individual classifiers within the ensemble. This paper challenges this assumption by showing that linear classifier obtained by various regularizations of the FLD can perform equally well as the ensemble. Moreover it demonstrates that using state of the art solvers linear classifiers can be trained more efficiently and offer certain potential advantages over the original ensemble leading to much lower computational complexity than the ensemble classifier. All claims are supported experimentally on a wide spectrum of stego schemes operating in both the spatial and JPEG domains with a multitude of rich steganalysis feature sets

Sludge-based activated carbon for removal of Cadmium in the water resource; Financial feasibility

Sludge-based activated carbon (AC) was prepared for the cadmium (Cd) removal from the aqueous solution. X-ray diffraction and Fourier transform infrared were applied as two main techniques to investigate the surface characterizations of the adsorbent. Response surface methodology (RSM), which was coupled with central composite design (CCD), was applied to study the impact of three major parameters, such as pH, dosage (D) and initial concentrate (C) on the percentage of Cadmium removal. The RSM model indicates that the optimum points of Cd removal were 90% at pH = 8.74 and D/C = 50. The Financial Feasibility and Investment Strategy was also investigated to consider key indicators in the financial feasibility of water treatment projects. The present study shows the systematic investigation of an attractive adsorbent to remove Cd from an aqueous solution. Also, in this study, modern investment strategies and efficient financing methods for water treatment projects are provided. The results showed that this type of adsorbent is appropriately able to eliminate Cd from water and aqueous solution

Computing Dependencies between DCT Coefficients for Natural Steganography in JPEG Domain

International audienc

Investigation of renal osteodystrophy among hemodialysis patients referring to Towhid Hospital, Sanandaj, Iran

BACKGROUND: Renal osteodystrophy is a major complication among dialysis patients that can lead to muscle weakness, and bone pain and fractures by minor trauma. In the present study, the frequency of these symptoms and status of blood markers among dialysis patients are discussed. METHODS: In a crass-sectional study, blood sample was obtained from 82 hemodialysis patients for calcium (Ca), phosphorus (P), alkaline phosphatase (ALP), and parathyroid hormone (PTH) level measurement. Radiography of the right hand was performed for 57 patients. Data analysis was performed via SPSS by using chi-square test, Fisher’s exact test, and Pearson correlation coefficient. RESULTS: The prevalence of osteodystrophy among dialysis patients was 72% (59 patients), including 29 patients with high bone turnover and 30 patients with adynamic bone disease. Moreover, 24 patients (29.3%) were hypocalcaemic and 25 patients (30.5%) were hypercalcemic. In addition, 25 (30.5%) patients had hyperphosphatemia. In the present study, 82 patients, 40 male (48.8%) and 42 female (51.2%), were recruited. Patients’ mean age ± standard deviation was 55.77 ± 14.99. There was a relation between increase in age and adynamic bone disease (P = 0.004). Calcium level had a significant association with radiologic manifestation of renal osteodystrophy (P = 0.007). PTH levels had moderate correlation with ALP level (r = 0.55). CONCLUSION: In the present study, there was a relation between age and adynamic bone disease; meaning that by increasing of age, the prevalence of adynamic bone disease also increased. There was a strong positive correlation between PTH and ALP.

Investigation of renal osteodystrophy among hemodialysis patients referring to Towhid Hospital, Sanandaj, Iran

BACKGROUND: Renal osteodystrophy is a major complication among dialysis patients that can lead to muscle weakness, and bone pain and fractures by minor trauma. In the present study, the frequency of these symptoms and status of blood markers among dialysis patients are discussed. METHODS: In a crass-sectional study, blood sample was obtained from 82 hemodialysis patients for calcium (Ca), phosphorus (P), alkaline phosphatase (ALP), and parathyroid hormone (PTH) level measurement. Radiography of the right hand was performed for 57 patients. Data analysis was performed via SPSS by using chi-square test, Fisher’s exact test, and Pearson correlation coefficient. RESULTS: The prevalence of osteodystrophy among dialysis patients was 72% (59 patients), including 29 patients with high bone turnover and 30 patients with adynamic bone disease. Moreover, 24 patients (29.3%) were hypocalcaemic and 25 patients (30.5%) were hypercalcemic. In addition, 25 (30.5%) patients had hyperphosphatemia. In the present study, 82 patients, 40 male (48.8%) and 42 female (51.2%), were recruited. Patients’ mean age ± standard deviation was 55.77 ± 14.99. There was a relation between increase in age and adynamic bone disease (P = 0.004). Calcium level had a significant association with radiologic manifestation of renal osteodystrophy (P = 0.007). PTH levels had moderate correlation with ALP level (r = 0.55). CONCLUSION: In the present study, there was a relation between age and adynamic bone disease; meaning that by increasing of age, the prevalence of adynamic bone disease also increased. There was a strong positive correlation between PTH and ALP

Effect of different levels of raisin waste on performance, nutrients digestibility and protozoal population of Mehraban growing lambs

The aim of this study was to assess the effects of different inclusion levels of raisin waste (RW) in the diet on the animal performance and ruminal fermentation parameters of growing lambs. Four levels of RW inclusion (i.e., R0, R1, R2 and R3 for 0, 100, 200 and 300 g RW kg-1 dry matter of diet, respectively) were tested. The experimental diets were fed to 24 male lambs (six months old) and six animals were allocated to each treatment. In the first experiment, effects of different levels of RW on the animals’ performance, some rumen parameters and protozoa populations were studied. In the second experiment, the apparent total tract digestibility of diets and nitrogen balance were measured. The highest final body weights were observed for the R2 and R3 diets. The R3 diet had the lowest dry matter intake (1156 vs. 1303 g day-1 for R3 and R0, respectively) and feed conversion rate (6.4 vs. 8.7 for R3 and R0, respectively). Total number of protozoa increased with the addition of RW, but Epidinium spp. completely disappeared with the R3diet. Inclusion of RW at levels higher than 200 g RW kg-1 DM of diet significantly reduced crude protein (p=0.042) and neutral detergent fiber digestibility (p=0.049). Our findings showed that RW could be included in the diets of growing lambs up to 200 g kg-1 DM without compromising their production performance

Content-adaptive pentary steganography using the multivariate generalized Gaussian cover model

International audienceThe vast majority of steganographic schemes for digital images stored in the raster format limit the amplitude of embedding changes to the smallest possible value. In this paper, we investigate the possibility to further improve the empirical security by allowing the embedding changes in highly textured areas to have a larger amplitude and thus embedding there a larger payload. Our approach is entirely model driven in the sense that the probabilities with which the cover pixels should be changed by a certain amount are derived from the cover model to minimize the power of an optimal statistical test. The embedding consists of two steps. First, the sender estimates the cover model parameters, the pixel variances, when modeling the pixels as a sequence of independent but not identically distributed generalized Gaussian random variables. Then, the embedding change probabilities for changing each pixel by 1 or 2, which can be transformed to costs for practical embedding using syndrome-trellis codes, are computed by solving a pair of non-linear algebraic equations. Using rich models and selection-channel-aware features, we compare the security of our scheme based on the generalized Gaussian model with pentary versions of two popular embedding algorithms: HILL and S-UNIWARD