VoIP profiler: Profiling voice over IP user communication behavior

Abstract

Understanding the user behavior in Voice over IP (VoIP) communication has twofold advantages. It helps in detecting anomalies and also helps in planning VoIP infrastructure deployment and optimization. Anomalies arise out of various attacks and misuses like flooding, malformed messages and spam messages. In this paper we propose VoIP Profiler a method for profiling the VoIP activities at user level. For profiling users we identify a set of parameters and compute statistics of these parameters for each user using VoIP traffic. Subsequently we use these parameters to classify users (and detect anomalies). We simulate an enterprise network and experiment with a large scale VoIP dataset and identify different types of users with high success rate. © 2016 IEEE.