Network Traffic Anomaly Detection and Prevention

1. Front Matter

   Pages i-xxii

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2. Introduction

   • Monowar H. Bhuyan, Dhruba K. Bhattacharyya, Jugal K. Kalita

   Pages 1-13

3. Networks and Network Traffic Anomalies

   • Monowar H. Bhuyan, Dhruba K. Bhattacharyya, Jugal K. Kalita

   Pages 15-69

4. A Systematic Hands-On Approach to Generate Real-Life Intrusion Datasets

   • Monowar H. Bhuyan, Dhruba K. Bhattacharyya, Jugal K. Kalita

   Pages 71-114

5. Network Traffic Anomaly Detection Techniques and Systems

   • Monowar H. Bhuyan, Dhruba K. Bhattacharyya, Jugal K. Kalita

   Pages 115-169

6. Alert Management and Anomaly Prevention Techniques

   • Monowar H. Bhuyan, Dhruba K. Bhattacharyya, Jugal K. Kalita

   Pages 171-199

7. Practical Tools for Attackers and Defenders

   • Monowar H. Bhuyan, Dhruba K. Bhattacharyya, Jugal K. Kalita

   Pages 201-242

8. Evaluation Criteria

   • Monowar H. Bhuyan, Dhruba K. Bhattacharyya, Jugal K. Kalita

   Pages 243-252

9. Open Issues, Challenges, and Conclusion

   • Monowar H. Bhuyan, Dhruba K. Bhattacharyya, Jugal K. Kalita

   Pages 253-257

10. Back Matter

    Pages 259-263

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This indispensable text/reference presents a comprehensive overview on the detection and prevention of anomalies in computer network traffic, from coverage of the fundamental theoretical concepts to in-depth analysis of systems and methods. Readers will benefit from invaluable practical guidance on how to design an intrusion detection technique and incorporate it into a system, as well as on how to analyze and correlate alerts without prior information.

Topics and features: introduces the essentials of traffic management in high speed networks, detailing types of anomalies, network vulnerabilities, and a taxonomy of network attacks; describes a systematic approach to generating large network intrusion datasets, and reviews existing synthetic, benchmark, and real-life datasets; provides a detailed study of network anomaly detection techniques and systems under six different categories: statistical, classification, knowledge-base, cluster and outlier detection, soft computing, and combination learners; examines alert management and anomaly prevention techniques, including alert preprocessing, alert correlation, and alert post-processing; presents a hands-on approach to developing network traffic monitoring and analysis tools, together with a survey of existing tools; discusses various evaluation criteria and metrics, covering issues of accuracy, performance, completeness, timeliness, reliability, and quality; reviews open issues and challenges in network traffic anomaly detection and prevention.

This informative work is ideal for graduate and advanced undergraduate students interested in network security and privacy, intrusion detection systems, and data mining in security. Researchers and practitioners specializing in network security will also find the book to be a useful reference.

• Anomaly Detection
• Data Mining
• Denial of Service
• Distributed Denial of Service
• Intrusion Prevention
• Network Attack
• Network Port Scan

• Kaziranga University, Jorhat, India

  Monowar H. Bhuyan

• Tezpur University, Napaam, India

  Dhruba K. Bhattacharyya

• University of Colorado, Colorado Springs, USA

  Jugal K. Kalita

Dr. Monowar H. Bhuyan is an Associate Professor and Head of the Department of Computer Science and Engineering at Kaziranga University, Jorhat, India. Dr. Dhruba K. Bhattacharyya is a Professor in the Department of Computer Science and Engineering at Tezpur University, India. Dr. Jugal K. Kalita is a Professor in the Department of Computer Science at the University of Colorado, Colorado Springs, CO, USA.

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