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Book Cover
E-book
Author Cua-Sánchez, Antonio, author

Title Traffic anomaly detection / Antonio Cua-Sánchez, Javier Aracil
Published London, UK ISTE, Ltd. Kidlington, Oxford, UK Elsevier, 2015
Online access available from:
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Description 1 online resource : illustrations
Contents ""Front Cover ""; ""Traffic Anomaly Detection ""; ""Copyright ""; ""Contents ""; ""Introduction ""
""2.3. Macroscopic Observation of Traffic """"2.4. Average-Day Analysis ""; ""2.5. Conclusion ""; ""Chapter 3: Comparative Analysis of Traffic Anomaly Detection Methods ""
""3.1. Introduction """"3.2. State of the Art ""; ""3.3. Average-Day Preliminary Analysis""; ""3.4. Proposed Change Point Detection Algorithms ""
""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) ""
""Chapter 2: Finding the Optimal Aggregation Period """"2.1. Introduction ""; ""2.2. State of the Art ""
Summary 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"
Bibliography Includes bibliographical references and index
Notes Online resource; title from PDF title page (EBSCO, viewed November 5, 2015)
Subject Computer networks.
Signal detection -- Mathematical models.
Signal detection -- Statistical methods.
Signal processing -- Mathematical models.
Signal processing -- Statistical methods.
Form Electronic book
Author Aracil, Javier, author
Ebooks Corporation.
ISBN 0081008074
9780081008072