Wireless Sensor Networks (WSNs) are a new technology foreseen to be used increasingly in the near future due to their data acquisition and data processing abilities. Security for WSNs is an area that needs to be considered in order to protect the functionality of these networks, the data they convey and the location of their members. The security models and protocols used in wired and other networks are not suited to WSNs because of their severe resource constraints, especially concerning energy . In this article, we propose a centralized intrusion detection scheme based on Support Vector Machines (SVMs) and sliding windows. We find that our system can detect black hole attacks and selective forwarding attacks with high accuracy without depleting the nodes of their energy.
S. Kaplantzis REF proposed a centralized intrusion detection scheme based on one-class SVM and sliding window.
Detecting Selective Forwarding Attacks in Wireless Sensor Networks using Support Vector Machines
2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information
2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information
Computer Science