May 01, 2011 to July 01, 2013
In traditional telecommunication, various experts estimate that fraud accounts for annual losses at an average of 5% of the operators’ revenue and still increasing at a rate of more than 10% yearly. Hence, with the openness and low cost structure of voice over IP (VoIP) service one can expect an even higher threat of fraud and higher losses of revenue making fraud and misuse of services one of the main challenges to VoIP providers. Fraud detection has been an active research and development area in the world of banking and credit card industry. In the VoIP area, there is still hardly any research or products that can assist providers in detecting anomalous behaviour. The main objective of this project is to offer a complete solution for automatic fraud detection that alarms providers when a suspicious behaviour is detected. Fraud detection and Intrusion detection that have traditionally been separate fields, will be combined in the context of SUNSHINE. The latter will explore the most recent research methods in the intrusion detection area and check their suitability for fraud detection, for instance, NN-SOM, Bayesian Networks, Markov Chains, and unsupervised methods such as profiling and clustering.