1,720,963 research outputs found

    On the Stability of the Information Carried by Traffic Flow Features at the Packet Level

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    This paper presents a statistical analysis of the amount of information that the features of traffic flows observed at the packet-level carry, with respect to the protocol that generated them. We show that the amount of information of the majority of such features remain constant irrespective of the point of observation (Internet core vs. Internet edge) and to the capture time (year 2000/01 vs. year 2008). We also describe a comparative analysis of how four statistical classifiers fare using the features we studied

    Support Vector Machines for TCP Traffic Classification

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    Support Vector Machines (SVM) represent one of the most promising Machine Learning (ML) tools that can be applied to the problem of traffic classification in IP networks. In the case of SVMs, there are still open questions that need to be addressed before they can be generally applied to traffic classifiers. Having being designed essentially as techniques for binary classification, their generalization to multi-class problems is still under research. Furthermore, their performance is highly susceptible to the correct optimization of their working parameters. In this paper we describe an approach to traffic classification based on SVM. We apply one of the approaches to solving multi-class problems with SVMs to the task of statistical traffic classification, and describe a simple optimization algorithm that allows the classifier to perform correctly with as little training as a few hundred samples. The accuracy of the proposed classifier is then evaluated over three sets of traffic traces, coming from different topological points in the Internet. Although the results are relatively preliminary, they confirm that SVM-based classifiers can be very effective at discriminating traffic generated by different applications, even with reduced training set sizes. (C) 2009 Elsevier B.V. All rights reserved

    Coarse Classification of Internet Traffic Aggregates

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    This paper introduces a new statistical classification technique that allows a coarse but effective estimation of the amount of bytes that different classes of protocols, such as Peer-to-Peer, web, e-mail, etc., carry over a given communication link. The technique works by observing only IP-level information and without requiring the reconstruction of transport-layer sessions, making it amenable to the monitoring of both clear-text and encrypted traffic aggregates. Results of practical experiments demonstrate that our coarse classifier can estimate with reasonable accuracy the amount of bytes carried on a communication link by a given traffic class both cumulatively and punctually, i.e., over both long and short time periods. Furthermore, preliminary results demonstrate the effectiveness of the technique in monitoring encrypted links, albeit under restrictive assumptions

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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