Traffic Anomaly Detection

Traffic Anomaly Detection 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".

1. Theoretical anomaly detection methods. Set of algorithms proposed for this analysis: the most used SCC (CUSUM), the two main tests of goodness-of-fit and Mutual Information.2. Finding the optimal aggregation period for a time series of Internet traffic3. Comparative analysis of traffic anomaly detection methods4. Proposal of a new information-theory based technique (typical day analysis)5. Conclusions

Scientific and Engineering communities working on Anomaly detection in the context of Network Security. In particular, early researchers, post-docs and engineers with an interest in this field.

He currently leads the Celtic NOTTS projectand co-leads the Customer Experience Management (CEM) Implementation Guide at the TeleManagement Forum.
Javier Aracil received the M.Sc. and Ph.D. degrees (Honors) from Technical University of Madrid in 1993 and 1995, both in Telecommunications Engineering. In 1995 he was awarded with a Fulbright scholarship and was appointed as a Postdoctoral Researcher of the Department of Electrical Engineering and Computer Sciences, University of California, Berkeley. In 1998 he was a research scholar at the Center for Advanced Telecommunications, Systems and Services of The University of Texas at Dallas. He has been an associate professor for University of Cantabria and Public University of Navarra and he is currently a full professor at Universidad Autónoma de Madrid, Madrid, Spain. His research interest are in optical networks and performance evaluation of communication networks. He has authored more than 100 papers in international conferences and journals.

• A new information-theory based technique for traffic anomaly detection (typical day analysis)
• Introductory chapters to anomaly detection methods including control charts, tests of goodness-of-fit Mutual Information
• Contains comparative analysis of traffic anomaly detection methods