A Framework for Monitoring SIP Enterprise Networks

摘要: In this paper we aim to enable security within SIP enterprise domains by providing monitoring capabilities at three levels: the network traffic, server logs and billing records. We propose an anomaly detection approach based on appropriate feature extraction one-class Support Vector Machines (SVM). methods for anomaly/attack type classification attack source identification. Our is validated through experiments a controlled test-bed using customized normal traffic generation model synthesized attacks. The results show promising performances in terms of accuracy, efficiency usability.