Skip to main content

Design of an Intrusion Detection System for Wireless Sensor Networks

Buy Article:

$113.00 plus tax (Refund Policy)


Wireless Sensor Networks (WSNs) have recently attracted a lot of interest in the research community for their wide range of applications. However, the WSN is vulnerable to numerous security attacks due to its features of open medium and dynamic topology. Many of the intrusion detection techniques developed on a fixed wired network are not applicable for WSNs. In this paper, we first propose a distributed and hierarchical intrusion detection system. There are mainly three entities exist in the system, which include Monitor, Communicator and Detector. The functionalities of these entities are described in detail. Then, a machine learning method using Hidden Markov Models is brought forward to detect abnormal events. Triple information is extracted from network traffic to train and test models, and the RP (Relative Probability) value is computed to classify normal and abnormal behaviors. The process of training and detection is introduced detailedly. Experiments demonstrate that the system is useful and effective to detect intrusive actions.


Document Type: Research Article


Publication date: 2011-10-01

More about this publication?
  • The growing interest and activity in the field of sensor technologies requires a forum for rapid dissemination of important results: Sensor Letters is that forum. Sensor Letters offers scientists, engineers and medical experts timely, peer-reviewed research on sensor science and technology of the highest quality. Sensor Letters publish original rapid communications, full papers and timely state-of-the-art reviews encompassing the fundamental and applied research on sensor science and technology in all fields of science, engineering, and medicine. Highest priority will be given to short communications reporting important new scientific and technological findings.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Terms & Conditions
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more