國立虎尾科技大學 |

Traffic anomaly detection

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Traffic anomaly detection/ Antonio Cua-Sánchez, Javier Aracil.
作者:	Cua-Sánchez, Antonio,
其他作者:	Aracil, Javier,
出版者:	London, UK :ISTE, Ltd. ; : 2015.,
面頁冊數:	1 online resource :ill. :
標題:	Signal detection - Statistical methods. -
電子資源:	https://www.sciencedirect.com/science/book/9781785480126
ISBN:	9780081008072 (electronic bk.)

Traffic anomaly detection
Cua-Sánchez, Antonio,

Traffic anomaly detection[electronic resource] /Antonio Cua-Sánchez, Javier Aracil. - London, UK :ISTE, Ltd. ;2015. - 1 online resource :ill.

Includes bibliographical references and index.

Front Cover -- Traffic Anomaly Detection -- Copyright -- Contents -- Introduction

This book presents an overview of traffic anomaly detection analysis, allowing you to monitor security aspects of multimedia services. The author's approach is based on the analysis of time aggregation adjacent periods of the traffic. As traffic varies throughout the day, it is essential to consider the concrete traffic period in which the anomaly occurs. This book presents the algorithms proposed specifically for this analysis and an empirical comparative analysis of those methods and settle a new information theory based technique, named "typical day analysis."

ISBN: 9780081008072 (electronic bk.)Subjects--Topical Terms:

1292683
Signal detection
--Statistical methods.Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: TK5102.5

Dewey Class. No.: 621.3822

Traffic anomaly detection
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245 1 0 $a Traffic anomaly detection $h [electronic resource] / $c Antonio Cua-Sánchez, Javier Aracil.
260 $a London, UK : $a Kidlington, Oxford, UK : $b ISTE, Ltd. ; $c 2015. $b Elsevier,
300 $a 1 online resource : $b ill.
504 $a Includes bibliographical references and index.
505 0 $a Front Cover -- Traffic Anomaly Detection -- Copyright -- Contents -- Introduction
505 8 $a Chapter 1: Introduction to Traffic Anomaly Detection Methods 1.1. Cumulative Sum Control Charts (CUSUM) -- 1.2. Tests of Goodness-of-fit -- 1.3. Mutual Information (MI)
505 8 $a Chapter 2: Finding the Optimal Aggregation Period 2.1. Introduction -- 2.2. State of the Art
505 8 $a 2.3. Macroscopic Observation of Traffic 2.4. Average-Day Analysis -- 2.5. Conclusion -- Chapter 3: Comparative Analysis of Traffic Anomaly Detection Methods
505 8 $a 3.1. Introduction 3.2. State of the Art -- 3.3. Average-Day Preliminary Analysis -- 3.4. Proposed Change Point Detection Algorithms
520 $a This book presents an overview of traffic anomaly detection analysis, allowing you to monitor security aspects of multimedia services. The author's approach is based on the analysis of time aggregation adjacent periods of the traffic. As traffic varies throughout the day, it is essential to consider the concrete traffic period in which the anomaly occurs. This book presents the algorithms proposed specifically for this analysis and an empirical comparative analysis of those methods and settle a new information theory based technique, named "typical day analysis."
588 0 $a Online resource; title from PDF title page (EBSCO, viewed November 5, 2015).
650 0 $a Signal detection $x Statistical methods. $3 1292683
650 0 $a Signal detection $x Mathematical models. $3 1292684
650 0 $a Signal processing $x Statistical methods. $3 598410
650 0 $a Signal processing $x Mathematical models. $3 632815
650 0 $a Computer networks. $3 528577
655 4 $a Electronic books. $2 local $3 554714
700 1 $a Aracil, Javier, $e author. $3 1292682
856 4 0 $u https://www.sciencedirect.com/science/book/9781785480126