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Traffic anomaly detection
~
Aracil, Javier,
Traffic anomaly detection
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Traffic anomaly detectionAntonio 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 detectionStatistical 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:
214203
Signal detection
--Statistical methods.Index Terms--Genre/Form:
214472
Electronic books.
LC Class. No.: TK5102.5
Dewey Class. No.: 621.3822
Traffic anomaly detection
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Front Cover -- Traffic Anomaly Detection -- Copyright -- Contents -- Introduction
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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)
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Chapter 2: Finding the Optimal Aggregation Period 2.1. Introduction -- 2.2. State of the Art
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2.3. Macroscopic Observation of Traffic 2.4. Average-Day Analysis -- 2.5. Conclusion -- Chapter 3: Comparative Analysis of Traffic Anomaly Detection Methods
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3.1. Introduction 3.2. State of the Art -- 3.3. Average-Day Preliminary Analysis -- 3.4. Proposed Change Point Detection Algorithms
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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."
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https://www.sciencedirect.com/science/book/9781785480126
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