Computer Intrusion Detection and Network Monitoring: A Statistical Viewpoint

Description

This book covers the basic statistical and analytical techniques of computer intrusion detection. It is aimed at both statisticians looking to become involved in the data analysis aspects of computer security and computer scientists looking to expand their toolbox of techniques for detecting intruders. The book is self-contained, assumng no expertise in either computer security or statistics. It begins with a description of the basics of TCP/IP, followed by chapters dealing with network traffic analysis, network monitoring for intrusion detection, host based intrusion detection, and computer viruses and other malicious code. Each section develops the necessary tools as needed. There is an extensive discussion of visualization as it relates to network data and intrusion detection. The book also contains a large bibliography covering the statistical, machine learning, and pattern recognition literature related to network monitoring and intrusion detection. David Marchette is a scientist at the Naval Surface Warfacre Center in Dalhgren, Virginia. He has worked at Navy labs for 15 years, doing research in pattern recognition, computational statistics, and image analysis. He has been a fellow by courtesy in the mathematical sciences department of the Johns Hopkins University since 2000. He has been working in conputer intrusion detection for several years, focusing on statistical methods for anomaly detection and visualization. Dr. Marchette received a Masters in Mathematics from the University of California, San Diego in 1982 and a Ph.D. in Computational Sciences and Informatics from George Mason University in 1996.

 

Table of Contents