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Robustness of the MarkovChain Model for CyberAttack Detection
 IEEE Trans. Reliability
, 2004
"... Abstract—Cyberattack detection is used to identify cyberattacks while they are acting on a computer and network system to compromise the security (e.g., availability, integrity, and confidentiality) of the system. This paper presents a cyberattack detection technique through anomalydetection, a ..."
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Cited by 19 (0 self)
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detection, and discusses the robustness of the modeling technique employed. In this technique, a Markovchain model represents a profile of computerevent transitions in a normal/usual operating condition of a computer and network system (a norm profile). The Markovchain model of the norm profile is generated from
Markov Chain Models . . .
, 1993
"... In recent research on extreme value statistics, there has been an extensive development of threshold methods, first in the univariate case but subsequently in the multivariate case as well. In this paper, we develop an alternative methodology for extreme values of univariate time series, by assuming ..."
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, by assuming that the time series is Markovian and using bivariate extreme value theory to suggest appropriate models for the transition distributions. We develop an alternative form of the likelihood representation for threshold methods, and then show how this can be applied to a Markovian time series. A
Numerical Methods in Markov Chain Modelling
 Operations Research
, 1996
"... This paper describes and compares several methods for computing stationary probability distributions of Markov chains. The main linear algebra problem consists of computing an eigenvector of a sparse, nonsymmetric, matrix associated with a known eigenvalue. It can also be cast as a problem of solvi ..."
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Cited by 36 (8 self)
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This paper describes and compares several methods for computing stationary probability distributions of Markov chains. The main linear algebra problem consists of computing an eigenvector of a sparse, nonsymmetric, matrix associated with a known eigenvalue. It can also be cast as a problem
Markovchain modeling for multicast signaling delay analysis
, 2004
"... Feedback signaling plays a key role in flow control because the traffic source relies on the signaling information to make correct and timely flowcontrol decisions. However, it is difficult to design an efficient signaling algorithm since a signaling message can tolerate neither error nor latency. ..."
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Cited by 15 (6 self)
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binarytree model and an independentmarking statistical model for multicastsignaling delay analysis. This paper considers a general scenario where the congestion markings at different links are dependent—a more accurate but complex case. Specifically, we develop a Markovchain model defined by the link
SpaceOptimized Markov Chain Model for File Prefetching
"... This project investigated the ability of a Markov Chain model to predict file access patterns in OceanStore, a globalscale storage system currently under development. Because a naive implementation of the transition matrix is an inefficient use of memory, we evaluated a simple sparsematrix techniq ..."
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Cited by 1 (0 self)
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This project investigated the ability of a Markov Chain model to predict file access patterns in OceanStore, a globalscale storage system currently under development. Because a naive implementation of the transition matrix is an inefficient use of memory, we evaluated a simple sparse
Weighted Markov Chain Model for Musical Composer Identification
"... Abstract. Several approaches based on the ‘Markov chain model ’ have been proposed to tackle the composer identification task. In the paper at hand, we propose to capture phrasing structural information from inter onset and pitch intervals of pairs of consecutive notes in a musical piece, by incorpo ..."
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Cited by 3 (1 self)
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Abstract. Several approaches based on the ‘Markov chain model ’ have been proposed to tackle the composer identification task. In the paper at hand, we propose to capture phrasing structural information from inter onset and pitch intervals of pairs of consecutive notes in a musical piece
A Markov Chain Model Checker
, 2000
"... . Markov chains are widely used in the context of performance and reliability evaluation of systems of various nature. Model checking of such chains with respect to a given (branching) temporal logic formula has been proposed for both the discrete [17, 6] and the continuous time setting [4, 8]. ..."
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Cited by 58 (22 self)
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. Markov chains are widely used in the context of performance and reliability evaluation of systems of various nature. Model checking of such chains with respect to a given (branching) temporal logic formula has been proposed for both the discrete [17, 6] and the continuous time setting [4, 8
Introducing Markov Chains Models to Undergraduates
 INTERNATIONAL STATISTICAL INSTITUTE, 53RD SESSION
, 2001
"... ..."
A Markov Chain Model of the BCell Algorithm
 PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON ARTIFICIAL IMMUNE SYSTEMS, VOLUME 3627 OF LNCS
, 2005
"... An exact Markov chain model of the Bcell algorithm (BCA) is constructed via a novel possible transit method. The model is used to formulate a proof that the BCA is convergent absolute under a very broad set of conditions. Results from a simple numerical example are presented, we use this to demonst ..."
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Cited by 9 (5 self)
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An exact Markov chain model of the Bcell algorithm (BCA) is constructed via a novel possible transit method. The model is used to formulate a proof that the BCA is convergent absolute under a very broad set of conditions. Results from a simple numerical example are presented, we use
Markov Chain Models of Genetic Algorithms
 In Proceedings of the Genetic and Evolutionary Computation (GECCO) conference
, 1999
"... Nix and Vose [Nix and Vose, 1992] modeled the simple genetic algorithm as a Markov chain, where the Markov chain states are populations. Vose has extended this model to a "Random Heuristic Search" model of genetic (and other) algorithms where each individual of the next generation is selec ..."
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Cited by 9 (1 self)
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Nix and Vose [Nix and Vose, 1992] modeled the simple genetic algorithm as a Markov chain, where the Markov chain states are populations. Vose has extended this model to a "Random Heuristic Search" model of genetic (and other) algorithms where each individual of the next generation
Results 1  10
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131,370