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In this paper a universal steganalysis scheme is proposed for images. The scheme is based on the characteristic function moments of three-level wavelet subbands including the further decomposition coefficients of the first scale diagonal subband. The first three order statistical moments of each band are selected to form a feature vector for steganalysis. The Euclidean distance is used as the separability...
Performance of some suboptimal detectors can be improved by adding independent noise to their observations. In this paper, the effects of adding independent noise to observations of a detector are investigated for binary composite hypothesis-testing problems in a generalized Neyman-Pearson framework. Sufficient conditions are derived to determine when performance of a detector can or cannot be improved...
Security of Web servers has become a sensitive subject today. Prediction of normal and abnormal request is problematic due to large number of false alarms in many anomaly based intrusion detection systems (IDS). SS-IDS derives automatically the parameter profiles from the analyzed data thereby generating the statistical signatures. Statistical signatures are based on modeling of normal requests and...
A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Bayes net. The quantitative aspects are the net parameters. This paper develops a hybrid criterion for learning Bayes net structures that is based on both aspects. We combine model selection criteria measuring data fit with correlation...
It is often the case in failure and anomaly investigations that data is either limited or so wide ranging that it is difficult to bring focus to a key root cause. For this reason, a disciplined approach incorporating root cause trees (Ishikawa Diagrams) is usually taken to develop and track root cause hypotheses and analyses. During the investigation, statistical tools can be used to evaluate various...
This paper investigates the application of statistical methods in performance analysis of multimodal biometric systems. It develops an efficient and systematic approach to evaluate system performance under the influence of errors. Based upon the proposed approach, 126 experiments are conducted with the BSSR1 dataset on typical fusion methods using different normalization techniques. Experiment results...
How to composite Web service is one the most important problems of next generation Internet (NGI) researching. In order to reuse complex service for service composition, multi-scale Web service composition (MSWC) is proposed. Inspired by word segmenting algorithm, service composition can be achieved by diving service request into several groups and mapping these groups into existed complex services...
Audio synthesis algorithms in general, are aimed at synthesizing audio based on target specifications or target descriptors with the requirement of natural-sounding results and correct content representation. However, work on synthesis algorithms in an audio quality enhancement context, is limited. In this paper, a new algorithm on audio synthesis is presented that attempts to improve the quality...
Traditionally, group testing is a design problem. The goal is to design an optimally efficient set of tests of items such that the test results contain enough information to determine a small subset of items of interest. It has its roots in the statistics community and was originally designed for the selective service during World War II to remove men with syphilis from the draft. It appears in many...
Text-steganography plays an increasingly significant role in covert-communication on Internet. Compared with study on text-steganography, research on text-steganalysis is in its infancy. In this paper, we present a statistical analysis of a kind of word-shift text-steganography by using neighbor difference (length difference of two consecutive spaces). We classify nature PDF documents into two cases...
We present a generic method for analyzing the effect of process variability in nanoscale circuits. The proposed framework uses kernel and a generic tail probability estimator to eliminate the need for a-priori density choice for the nature of circuit variation. This allows capturing the true nature of the circuit variation from a few random samples of its observed responses. The data-driven, non-parametric,...
Many locally optimum, sub-optimum and ad hoc detectors exploit knowledge of the noise probability density function (PDF) to obtain their test statistic for the detection of stochastic signals in non-Gaussian noise and appear to offer potential for highly improved performance for very small signal to noise ratios. The authors explore the realism of this conclusion by comparing performance of a locally...
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