Abstract
Voice over Internet Protocol (VoIP) is an emerging communication service that has advanced in ubiquitous computing environments. Although VoIP is inexpensive and offers additional services, there has been little provision for attacks at the weak points. With the advances of Wireless Sensor Network (WSN) technologies, the risk is increasing. Due to the resource constraints of WSN, attacks have become easier, making protection of the network more difficult. In this work, we attempt to distinguish fraud call attacks as outliers from normal calls on the basis of call detail records. We adopted and applied a Local Outlier Factor (LOF) method on real call data, which include actual fraud call attacks. Our results show the outlier detection method can be effective in detecting fraud calls. Moreover, introducing two additional attributes related to fraud call characteristics enhanced the detection performance.
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