Probabilistic techniques for intrusion detection based on computeraudit data

This paper presents a series of studies on probabilistic properties of activity data in an information system for detecting intrusions into the information system. Various probabilistic techniques of intrusion detection, including decision tree, Hotelling's T² test, chi-square multivariate test, and Markov chain are applied to the same training set and the same testing set of computer audit data for investigating the frequency property and the ordering property of computer audit data. The results of these studies provide answers to several questions concerning which properties are critical to intrusion detection. First, our studies show that the frequency property of multiple audit event types in a sequence of events is necessary for intrusion detection. A single audit event at a given time is not sufficient for intrusion detection. Second, the ordering property of multiple audit events provides additional advantage to the frequency property for intrusion detection. However, unless the scalability problem of complex data models taking into account the ordering property of activity data is solved, intrusion detection techniques based on the frequency property provide a viable solution that produces good intrusion detection performance with low computational overhead     

Interferential lithography of 1D thin metallic sinusoidal gratings: Accurate control of the profile for azimuthal angular dependent plasmonic effects and applications

Nonlinear processes involved in the manufacture of nominally sinusoidal surface relief diffraction gratings generated by interference lithography can introduce distortions into the profile of these surfaces. Such distortions may dramatically affect both the specular reflectivity and diffracted efficiencies from such a surface [H. Raether, Phys. Thin Film 9 (1977) 145–261]. We shall consider in particular the case of metallic gratings used to investigate plasmonic effects that can be engineered for bio-sensing applications. To investigate these effects, interference lithography (IL) has been used for the generation of profile controlled sinusoidal plasmonic crystals. IL exposure contrast study has been performed to control the amplitude oscillation and the surface roughness quality. Bi-metallic layer of silver and gold have been systematically deposited with different film thicknesses. A comprehensive numerical model that studies the optical coupling to surface plasmon polaritons on Ag/Au gratings has been undertaken for the simulation of the reflectivity and azimuthal angle dependence [Z. Chen, I.R. Hooper, J.R. Sambles, J. Opt. A: Pure Appl. Opt. 10 (1) (2008) 015007]. This computation illustrates the sensitivity of individual features to specific harmonic components of the surface, for surface plasmon resonances recorded in both the zeroth and higher diffracted orders. The roughness surface control after development and after bi-metallic evaporation strongly contributes to tighten the width of the reflectivity peak. Optimization process has shown that for an Ag (37 nm) and Au (7 nm) metallic bilayer, a semi-amplitude of 20 nm provides the best reflectivity.     

Direct and gradient-based average strain estimation by using weighted nearest neighbor cross-correlation peaks

In this paper, two novel approaches, gradientbased and direct strain estimation techniques, are proposed for high-quality average strain imaging incorporating a cost function maximization. Stiffness typically is a continuous function. Consequently, stiffness of proximal tissues is very close to that of the tissue corresponding to a given data window. Hence, a cost function is defined from exponentially weighted neighboring pre- and post-compression RF echo normalized cross-correlation peaks in the lateral (for displacement estimation) or in both the axial and the lateral (for direct strain estimation) directions. This enforces a controlled continuity in displacement/strain and average displacement/strain is calculated from the corresponding maximized cost function. Axial stress causes lateral shift in the tissue. Therefore, a 1-D post-compression echo segment is selected by incorporating Poisson's ratio. Two stretching factors are considered simultaneously in gradient-based strain estimation that allow imaging the lesions properly. The proposed time-domain gradient-based and direct-strain-estimation-based algorithms demonstrate significantly better performance in terms of elastographic signal-to-noise ratio (SNRe), elastographic contrast-to-noise ratio (CNRe), peak signal-to-noise ratio (PSNR), and mean structural similarity (MSSIM) than the other reported time-domain gradientbased and direct-strain-estimation techniques in finite element modeling (FEM) simulation and phantom experiments. For example, in FEM simulation, it has been found that the proposed direct strain estimation method can improve up to approximately 2.49 to 8.71, 2.2 to 6.63, 1.5 to 5, and 1.59 to 2.45 dB in the SNRe, CNRe, PSNR, and MSSIM compared with the traditional direct strain estimation method, respectively, and the proposed gradient-based algorithm demonstrates 2.99 to 16.26, 18.74 to 23.88, 3 to 9.5, and 0.6 to 5.36 dB improvement in the SNRe, CNRe, PSNR, and MSSIM, respectively, compared with a recently reported time-domain gradient-based technique. The range of improvement as noted above is for low to high applied strains. In addition, the comparative results using the in vivo breast data (including malignant or benign masses) also show that the lesion size is better defined by the proposed gradient-based average strain estimation technique.     

Application of Bernoulli matrix method for solving two-dimensional hyperbolic telegraph equations with Dirichlet boundary conditions

The present article is devoted to develop a new approach and methodology to find the approximate solution of second order two-dimensional telegraph equations with the Dirichlet boundary conditions. We first transform the telegraph equations into equivalent partial integro-differential equations (PIDEs) which contain both initial and boundary conditions and therefore can be solved numerically in a more appropriate manner. Operational matrices of integration and differentiation of Bernoulli polynomials together with the completeness of these polynomials are used to reduce the PIDEs into the associated algebraic generalized Sylvester equations which can be solved by an efficient Krylov subspace iterative (i.e., BICGSTAB) method. The efficiency of the proposed method has been confirmed with several test examples and it is clear that the results are acceptable and found to be in good agreement with exact solutions. We have compared the numerical results of the proposed method with radial basis function method and differential quadrature method. Also, the method is simple, efficient and produces very accurate numerical results in considerably small number of basis functions and hence reduces computational effort. Moreover, the technique is easy to apply for multidimensional problems.     

Modal Hermite spectral collocation method for solving multi-dimensional hyperbolic telegraph equations

The present research is contemplated proposing a numerical solution of multi-dimensional hyperbolic telegraph equations with appropriate initial time and boundary space conditions. The truncated Hermite series with unknown coefficients are used for approximating the solution in both of the spatial and temporal variables. The basic idea for discretizing the considered one-dimensional (1D), two-dimensional (2D) and three-dimensional (3D) telegraph equations is based on the collocation method together with the Hermite operational matrices of derivatives. The resulted systems of linear algebraic equations are solved by some efficient methods such as LU factorization. The solution of the algebraic system contains the coefficients of the truncated Hermite series. Numerical experiments are provided to illustrate the accuracy and efficiency of the presented numerical scheme. Comparisons of numerical results associated to the proposed method with some of the existing numerical methods confirm that the method is accurate and fast experimentally.     

Data envelopment analysis and robust optimization: A review

This paper reviews the milestone approaches for handling uncertainty in data envelopment analysis (DEA). This paper presents the detailed classifications of robust data envelopment analysis (RDEA). RDEA is appropriate for measuring the efficiencies of decision-making units in the presence of the data and distributional uncertainties. This paper reviews scenario-based and uncertainty set of DEA models. It covers 73 studies from 2008 to 2019. The paper concludes with suggestions about the guidelines for future researches in the field of RDEA.     

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A co-processor design to accelerate sequential monocular SLAM EKF process

Extended Kalman Filter (EKF) is a non-linear state estimation technique which is used to produce values that close to the true value when given with measurement containing noise and other inaccuracies. In Monocular Simultaneous Localization and Mapping (SLAM), EKF is used to estimate position and motion information. In this paper, Monocular SLAM software implementation on a general purpose computer is studied to find the most time consuming part of the estimation program. The analysis concentrates on the Monocular SLAM EKF estimation process which involves prediction, measurement prediction, matching and update. For this purpose, a form of dynamic programming analysis tool called software profiling is utilized to determine which section of the estimation program demands the highest processing time. Based on the analysis, it is found that EKF “matching” process contribute to the highest computation time. The reason behind the time-consuming process is because for every predicted feature in the matching stage, the acceptance region and their cross correlation have to be calculated. In a typical general purpose computer software implementation, the processing is limited to sequences of operations (i.e. sequential processing). Such implementation will delay the next process until the prior process completed. However, further analysis conducted in this paper shows that each feature does not depend on the prior process and can be processed individually. This would allow several features to be processed simultaneously to improve the execution speed. Therefore, an FPGA pipelined and parallel processing architecture is proposed.