Network Anomaly Detection
A Machine Learning Perspective
1st Edition
Published on 18. June 2013
366 pages
978-1-4665-8209-5 (ISBN)
Description
With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavi
More details
Language
English
Place of publication
Philadelphia, PA
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Illustrations
71 s/w Abbildungen, 42 s/w Tabellen
71 b/w images and 42 tables
File size
3,61 MB
ISBN-13
978-1-4665-8209-5 (9781466582095)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Dhruba Kumar Bhattacharyya | Jugal Kumar Kalita
Network Anomaly Detection
A Machine Learning Perspective
Book
06/2013
1st Edition
CRC Press
€166.80
Shipment within 15-20 days
Persons
Dhruba Kumar Bhattacharyya is a professor in computer science and engineering at Tezpur University. Professor Bhattacharyya's research areas include network security, data mining, and bioinformatics. He has published more than 180 research articles in leading international journals and peer-reviewed conference proceedings. Dr. Bhattacharyya has written or edited seven technical books in English and two technical reference books in Assamese. He is on the editorial board of several international journals and has also been associated with several international conferences. For more about Dr. Bhattacharyya, see his profile at Tezpur University.
Jugal Kumar Kalita teaches computer science at the University of Colorado, Colorado Springs. His expertise is in the areas of artificial intelligence and machine learning, and the application of techniques in machine learning to network security, natural language processing, and bioinformatics. He has published 115 papers in journals and refereed conferences, and is the author of a book on Perl. He received the Chancellor's Award at the University of Colorado in 2011, in recognition of lifelong excellence in teaching, research, and service. For more about Dr. Kalita, see his profile at the University of Colorado.
Jugal Kumar Kalita teaches computer science at the University of Colorado, Colorado Springs. His expertise is in the areas of artificial intelligence and machine learning, and the application of techniques in machine learning to network security, natural language processing, and bioinformatics. He has published 115 papers in journals and refereed conferences, and is the author of a book on Perl. He received the Chancellor's Award at the University of Colorado in 2011, in recognition of lifelong excellence in teaching, research, and service. For more about Dr. Kalita, see his profile at the University of Colorado.
Content
Introduction. Networks and Anomalies. An Overview of Machine Learning Methods. Detecting Anomalies in Network Data. Feature Selection. Approaches to Network Anomaly Detection. Evaluation Methods. Tools and Systems. Discussion. Open Issues, Challenges and Concluding Remarks. References. Index.
