Use of an artificial neural network to detect anomalies in wireless device location for the purpose of intrusion detection

Summary form only given. This work proposes that wireless signals can be monitored for potential intruders based on signal-sensing, and presents a framework methodology for implementing such a system. By identifying potential threats in this way, actions could be taken early before the intruder has had the opportunity to compromise the network. On the leading edge of intrusion detection, and the focus of this research, is in the application of intelligent technology to predict patterns of anomalies that may point to deviant behavior. The specific goal is the proposal of applying an artificial neural network (ANN) or other intelligent system for the use of monitoring wireless radio signals to detect location trends. The typical wireless network user will use their device in a predictable pattern of locations. It would be possible to map the physical locations of users and train an intelligent system with existing location patterns. By developing the established usage information, it would then be possible for the intelligent system to pinpoint anomalies in wireless location.