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Network Traffic Anomaly Detection and Prevention

Concepts, Techniques, and Tools

  • Textbook
  • © 2017

Overview

Authors:
  1. Monowar H. Bhuyan

    1. Kaziranga University, Jorhat, India

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  2. Dhruba K. Bhattacharyya

    1. Tezpur University, Napaam, India

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  3. Jugal K. Kalita

    1. University of Colorado, Colorado Springs, USA

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  • Provides a thorough introduction to network attacks, describes the pros and cons of various data mining approaches, and discusses important issues and challenges to be addressed
  • Presents a systematic, hands-on approach to generating real-life large intrusion datasets
  • Contains lists of practical tools and systems, together with hands-on examples for launching, monitoring, detecting, and preventing various types of network attacks

Part of the book series: Computer Communications and Networks (CCN)

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Table of contents (8 chapters)

  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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Keywords

About this book

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.

Authors and Affiliations

  • Kaziranga University, Jorhat, India

    Monowar H. Bhuyan

  • Tezpur University, Napaam, India

    Dhruba K. Bhattacharyya

  • University of Colorado, Colorado Springs, USA

    Jugal K. Kalita

About the authors

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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