The Experts below are selected from a list of 231 Experts worldwide ranked by ideXlab platform
Hirosuke Yamamoto - One of the best experts on this subject based on the ideXlab platform.
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unsupervised anomaly detection within non Numerical Sequence data by average index difference with application to masquerade detection
Applied Stochastic Models in Business and Industry, 2014Co-Authors: Stefan Jan Skudlarek, Hirosuke YamamotoAbstract:Anomaly detection within non-Numerical Sequence data has developed into an important topic of data mining, but comparatively little research has been done regarding anomaly detection without training data unsupervised anomaly detection. One application found in computer security is the detection of a so-called masquerade attack, which consists of an attacker abusing a regular account. This leaves only the session input, which is basically a string of non-Numerical commands, for analysis. Our previous approach to this problem introduced the use of the so-called average index difference function for mapping the non-Numerical symbol data to a Numerical space. In the present paper, we examine the theoretical properties of the average index difference function, present an enhanced unsupervised anomaly detection algorithm based on the average index difference function, show the parameters to be theoretically inferable, and evaluate the performance using real-world data. Copyright © 2014 John Wiley & Sons, Ltd.
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Representative Sequence selection in unsupervised anomaly detection using spectrum kernel with theoretical parameter setting
2010 International Conference on Machine Learning and Cybernetics, 2010Co-Authors: Stefan Jan Skudlarek, Hirosuke YamamotoAbstract:Unsupervised anomaly detection is an important topic of data mining research, especially with respect to non-Numerical Sequence data. However, the majority of previous algorithms features empirical parameter selection. The contribution of this study is twofold: First, we show how the Akaike Information Criterion can be used to set the parameter of the spectrum kernel. Second, a distance-based algorithm for one-class unsupervised anomaly detection is presented. The algorithm uses the distance matrix of the data to select a Sequence representative of the normal class by means of robust statistics. The proposed algorithm is applied to two kinds of Sequence data, showing its suitability.
P. A. M. Dos Santos - One of the best experts on this subject based on the ideXlab platform.
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Digital holographic moiré pattern for optical Numerical code generation
Proceedings of SPIE, 2014Co-Authors: G. N. De Oliveira, M. E. De Oliveira, R. B. Da Rocha Freire, P. A. M. Dos SantosAbstract:In the present paper low frequency moire fringe patterns are used as secure Numerical code generator. These moire patterns are experimentally obtained by the superposition of two sinusoidal gratings with slightly different pitches. The Bi 12 TiO 20 photorefractive crystal sample is used as holographic medium An optical Numerical base was defined with patterns representing 0,1 and -1 digits like bits. Then, the complete set of these optical bits are combined to form bytes, where a Numerical Sequence is represented. The results show that the proposed Numerical code could be used as standard Numerical identification in robotic vision or in transmition of security Numerical keys.
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Photorefractive holographic moiré-like patterns for secure Numerical code generation
Optics Letters, 2013Co-Authors: G. N. De Oliveira, M. E. De Oliveira, P. A. M. Dos SantosAbstract:In this Letter, low-frequency photorefractive holographic moire fringe patterns are proposed as secure Numerical code generators that could be useful for storage or data transmission. These dynamic moire patterns are holographically obtained by the superposition of two or more sinusoidal gratings with slightly different pitches. The Bi12TiO20 photorefractive crystal sample is used as holographic medium. An optical Numerical base was defined with patterns representing the 0, 1 and −1 digits as bits. Then, the complete set of these optical bits is combined to form bytes, where a Numerical Sequence is represented. The results show that the proposed Numerical code is simple, robust and extremely secure, then could be used efficiently as standard Numerical identification in robotic vision or eventually in storage or transmission of secure Numerical data.
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Photorefractive moiré like pattern as optical Numerical code generator
Proceedings of SPIE, 2012Co-Authors: G. N. De Oliveira, M. E. De Oliveira, P. A. M. Dos SantosAbstract:In the present letter low frequency moire fringe patterns are used as secure Numerical code generator. These moire patterns are experimentally obtained by the superposition of two sinusoidal gratings with slightly different pitches. The Bi12TiO20 photorefractive crystal sample is used as holographic medium An optical Numerical base was defined with patterns representing 0,1 and -1 digits like bits. Then, the complete set of these optical bits are combined to form bytes, where a Numerical Sequence is represented. The results show that the proposed Numerical code could be used as standard Numerical identification in robotic vision or in transmition of security Numerical keys.
A. Pugliese - One of the best experts on this subject based on the ideXlab platform.
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Fast detection of XML structural similarity
IEEE Transactions on Knowledge and Data Engineering, 2005Co-Authors: S. Flesca, G. Manco, E. Masciari, L. Pontieri, A. PuglieseAbstract:Because of the widespread diffusion of semistructured data in XML format, much research effort is currently devoted to support the storage and retrieval of large collections of such documents. XML documents can be compared as to their structural similarity, in order to group them into clusters so that different storage, retrieval, and processing techniques can be effectively exploited. In this scenario, an efficient and effective similarity function is the key of a successful data management process. We present an approach for detecting structural similarity between XML documents which significantly differs from standard methods based on graph-matching algorithms, and allows a significant reduction of the required computation costs. Our proposal roughly consists of linearizing the structure of each XML document, by representing it as a Numerical Sequence and, then, comparing such Sequences through the analysis of their frequencies. First, some basic strategies for encoding a document are proposed, which can focus on diverse structural facets. Moreover, the theory of discrete Fourier transform is exploited to effectively and efficiently compare the encoded documents (i.e., signals) in the domain of frequencies. Experimental results reveal the effectiveness of the approach, also in comparison with standard methods.
S.r. Kulkarni - One of the best experts on this subject based on the ideXlab platform.
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Density estimation from an individual Numerical Sequence
Proceedings. 1998 IEEE International Symposium on Information Theory (Cat. No.98CH36252), 1998Co-Authors: A.b. Nobel, G. Morvai, S.r. KulkarniAbstract:The article considers univariate density estimation from an individual Numerical Sequence. It is assumed that (i) the limiting relative frequencies of the Numerical Sequence are governed by an unknown density, and (ii) there is a known upper bound for the variation of the density an an increasing Sequence of intervals. A simple estimation scheme is proposed, and its L/sub 1/ consistency is established when (i) and (ii) apply. In addition it is shown that there is no consistent estimation scheme for the set of individual Sequences satisfying only condition (i).
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Density estimation from an individual Numerical Sequence
IEEE Transactions on Information Theory, 1998Co-Authors: A.b. Nobel, G. Morvai, S.r. KulkarniAbstract:This paper considers estimation of a univariate density from an individual Numerical Sequence. It is assumed that (1) the limiting relative frequencies of the Numerical Sequence are governed by an unknown density, and (2) there is a known upper bound for the variation of the density on an increasing Sequence of intervals. A simple estimation scheme is proposed, and is shown to be L/sub 1/ consistent when (1) and (2) apply. In addition, it is shown that there is no consistent estimation scheme for the set of individual Sequences satisfying only condition (1).
Vincent J Hilser - One of the best experts on this subject based on the ideXlab platform.
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a horizontal alignment tool for Numerical trend discovery in Sequence data application to protein hydropathy
PLOS Computational Biology, 2013Co-Authors: Omar Hadzipasic, James O Wrabl, Vincent J HilserAbstract:An algorithm is presented that returns the optimal pairwise gapped alignment of two sets of signed Numerical Sequence values. One distinguishing feature of this algorithm is a flexible comparison engine (based on both relative shape and absolute similarity measures) that does not rely on explicit gap penalties. Additionally, an empirical probability model is developed to estimate the significance of the returned alignment with respect to randomized data. The algorithm's utility for biological hypothesis formulation is demonstrated with test cases including database search and pairwise alignment of protein hydropathy. However, the algorithm and probability model could possibly be extended to accommodate other diverse types of protein or nucleic acid data, including positional thermodynamic stability and mRNA translation efficiency. The algorithm requires only Numerical values as input and will readily compare data other than protein hydropathy. The tool is therefore expected to complement, rather than replace, existing Sequence and structure based tools and may inform medical discovery, as exemplified by proposed similarity between a chlamydial ORFan protein and bacterial colicin pore-forming domain. The source code, documentation, and a basic web-server application are available.
