A Weighted-Dissimilarity-Based Anomaly Detection Method for Mobile Wireless Networks
Ihn-Han Bae, Stephan Olariu · 2009
Mobile wireless networks continue to be plagued by theft of identity and intrusion. Both problems can be addressed in two different ways, either by misuse detection or anomaly-based detection. In this paper, we propose a weighted-dissimilarity-based anomaly detection method that can effectively identify abnormal behavior such as mobility patterns of mobile wireless networks. In the proposed algorithm, a normal profile is constructed from normal mobility patterns of mobile nodes in mobile wireless networks. From the constructed normal profile, the dissimilarity is computed by a weighted dissimilarity measure. If the computed dissimilarity value is greater than the dissimilarity threshold that is a system parameter, an alert message is occurred. The performance of the proposed method is evaluated through a simulation. From the result of the simulation, we know that the proposed method is superior to the performance of anomaly detection methods using other dissimilarity measures.