Network Anomaly Detection
Crc Press Inc (Verlag)
978-1-4665-8208-8 (ISBN)
In this book, you’ll learn about:
Network anomalies and vulnerabilities at various layers
The pros and cons of various machine learning techniques and algorithms
A taxonomy of attacks based on their characteristics and behavior
Feature selection algorithms
How to assess the accuracy, performance, completeness, timeliness, stability, interoperability, reliability, and other dynamic aspects of a network anomaly detection system
Practical tools for launching attacks, capturing packet or flow traffic, extracting features, detecting attacks, and evaluating detection performance
Important unresolved issues and research challenges that need to be overcome to provide better protection for networks
Examining numerous attacks in detail, the authors look at the tools that intruders use and show how to use this knowledge to protect networks. The book also provides material for hands-on development, so that you can code on a testbed to implement detection methods toward the development of your own intrusion detection system. It offers a thorough introduction to the state of the art in network anomaly detection using machine learning approaches and systems.
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.
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.
Zusatzinfo | 42 Tables, black and white; 71 Illustrations, black and white |
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Verlagsort | Bosa Roca |
Sprache | englisch |
Maße | 156 x 234 mm |
Gewicht | 657 g |
Themenwelt | Informatik ► Netzwerke ► Sicherheit / Firewall |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
Mathematik / Informatik ► Mathematik ► Logik / Mengenlehre | |
Recht / Steuern ► Privatrecht / Bürgerliches Recht ► IT-Recht | |
Technik ► Elektrotechnik / Energietechnik | |
ISBN-10 | 1-4665-8208-1 / 1466582081 |
ISBN-13 | 978-1-4665-8208-8 / 9781466582088 |
Zustand | Neuware |
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