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Network Anomaly Detection: A Machine Learning Perspective - Research Book

Network Anomaly Detection: A Machine Learning Perspective - Research Book

Latest Research Book in Network Anomaly Detection: A Machine Learning Perspective

Author(s) Name:  Dhruba Kumar Bhattacharyya, Jugal Kumar Kalita

About the Book:

   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 behavior.
   Finding these anomalies has extensive applications in areas such as cyber security, credit card and insurance fraud detection, and military surveillance for enemy activities. Network Anomaly Detection: A Machine Learning Perspective presents machine learning techniques in depth to help you more effectively detect and counter network intrusion.

Table of Contents

  • Introduction
  • Networks and Anomalies
  • Networks and Anomalies
  • Detecting Anomalies in Network Data
  • Feature Selection
  • Approaches to Network Anomaly Detection
  • Evaluation Methods
  • Tools and Systems
  • Open Issues, Challenges and Concluding Remarks
  • ISBN:  9781466582088

    Publisher:  Chapman and Hall/CRC Publisher

    Year of Publication:  2013

    Book Link:  Home Page Url