Search
Home  |  About Us  |  Contact Us  |  Authors  |  Orders  |  Email Alerts  |  E-Catalogues  |  Exhibitions  |  Journals  |  E-books
  BOOKS BY SUBJECT
  Architecture and Building
Management

Asian Studies
Business and Management
Chemistry
Computer Science
Economics and Finance
Engineering
Environmental Science
General Interest
History of Science
Life Sciences
Materials Science
Mathematics
Medicine and Healthcare
Nanotechnology and
Nanoscience

Nonlinear Science
Physics
Popular Science
Social Sciences
New Titles
New Reviews
 

INTRUSION DETECTION
A Machine Learning Approach

by Jeffrey J P Tsai (University of Illinois, Chicago, USA & Asia University, Taiwan)

This important book introduces the concept of intrusion detection, discusses various approaches for intrusion detection systems (IDS), and presents the architecture and implementation of IDS. It emphasizes on the prediction and learning algorithms for intrusion detection and highlights techniques for intrusion detection of wired computer networks and wireless sensor networks. The performance comparison of various IDS via simulation will also be included.

 
Contents:
  • Intrusion Detection Model
  • Problem and Challenges
  • System Architecture
  • Labeling Tools
  • Detection Model
  • Predication Model and Learning Algorithm
  • Model Tuning Algorithm
  • Fuzzy IDS Systems
  • Dual-Adaptive Intrusion Detection Model
  • Intrusion Detection of Wireless Sensor Networks
  • Performance Evaluation
 
Readership: Academicians, researchers and graduate students in software engineering/programming; computer engineering, knowledge and system engineering.
 
 
300pp (approx.)    Pub. date: Scheduled Winter 2010  
ISBN:   978-1-84816-447-5
1-84816-447-5
   US$111 / £76

 


 
 

Follow ImperialCPress on Twitter
Copyright © 2010 Imperial College Press Co. All rights reserved.