Applications of Data Mining in Computer Security

  • Daniel Barbará
  • Sushil Jajodia
Part of the Advances in Information Security book series (ADIS, volume 6)

Table of contents

  1. Front Matter
    Pages i-xx
  2. Steven Noel, Duminda Wijesekera, Charles Youman
    Pages 1-31
  3. Klaus Julisch
    Pages 33-62
  4. Daniel Barbará, Julia Couto, Sushil Jajodia, Ningning Wu
    Pages 63-76
  5. Eleazar Eskin, Andrew Arnold, Michael Prerau, Leonid Portnoy, Sal Stolfo
    Pages 77-101
  6. Oliver Dain, Robert K. Cunningham
    Pages 103-122
  7. Xinzhou Qin, Wenke Lee, Lundy Lewis, João B. D. Cabrera
    Pages 123-151
  8. Andrew Honig, Andrew Howard, Eleazar Eskin, Sal Stolfo
    Pages 153-193
  9. João B. D. Cabrera, Lundy Lewis, Xinzhou Qin, Wenke Lee, Raman K. Mehra
    Pages 195-227
  10. Olivier de Vel, Alison Anderson, Mal Corney, George Mohay
    Pages 229-250
  11. Back Matter
    Pages 251-252

About this book

Introduction

Data mining is becoming a pervasive technology in activities as diverse as using historical data to predict the success of a marketing campaign, looking for patterns in financial transactions to discover illegal activities or analyzing genome sequences. From this perspective, it was just a matter of time for the discipline to reach the important area of computer security. Applications Of Data Mining In Computer Security presents a collection of research efforts on the use of data mining in computer security.

Applications Of Data Mining In Computer Security concentrates heavily on the use of data mining in the area of intrusion detection. The reason for this is twofold. First, the volume of data dealing with both network and host activity is so large that it makes it an ideal candidate for using data mining techniques. Second, intrusion detection is an extremely critical activity. This book also addresses the application of data mining to computer forensics. This is a crucial area that seeks to address the needs of law enforcement in analyzing the digital evidence.

Keywords

Information Variable architecture data mining genome knowledge security

Editors and affiliations

  • Daniel Barbará
    • 1
  • Sushil Jajodia
    • 1
  1. 1.George Mason UniversityUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-0953-0
  • Copyright Information Kluwer Academic Publishers 2002
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-5321-8
  • Online ISBN 978-1-4615-0953-0
  • Series Print ISSN 1568-2633
  • About this book