Network anomaly detection : a machine learning perspective / Dhruba Kumar Bhattacharyya, Jugal Kumar Kalita.

Includes bibliographical references (pages 295-336) and index

1. Introduction -- 2. Networks and anomalies -- 3. An overview of machine learning methods -- 4. Detecting anomalies in network data -- 5. Feature selection -- 6. Approaches to network anomaly detection -- 7. Evaluation methods -- 8. Tools and systems -- 9. Open issues, challenges and concluding remarks

"This book discusses detection of anomalies in computer networks from a machine learning perspective. It introduces readers to how computer networks work and how they can be attacked by intruders in search of fame, fortune, or challenge. The reader will learn how one can look for patterns in captured network traffic data to look for anomalous patterns that may correspond to attempts at unauthorized intrusion. The reader will be given a technical and sophisticated description of such algorithms and their applications in the context of intrusion detection in networks"-- Provided by publisher

Also available in print format