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".
- 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
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".
- 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
![Traffic Anomaly Detection](http://img.images-bn.com/static/redesign/srcs/images/grey-box.png?v11.11.4)
Traffic Anomaly Detection
70![Traffic Anomaly Detection](http://img.images-bn.com/static/redesign/srcs/images/grey-box.png?v11.11.4)
Traffic Anomaly Detection
70eBook
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Product Details
ISBN-13: | 9780081008072 |
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Publisher: | Elsevier Science |
Publication date: | 10/31/2015 |
Sold by: | Barnes & Noble |
Format: | eBook |
Pages: | 70 |
File size: | 3 MB |