A hybrid system for fraud detection in mobile communications

During the course of the European project \Advanced Security for Personal Communication Technologies" (ASPeCT), we have developed some rule-based and neural network architectures as a number of di erent fraud detection tools for GSM networks. We have now integrated these di erent techniques into a hybrid detection tool. We optimized the performance of the hybrid system in terms of the number of subscribers raising alarms. More precisely, we optimized performance curves showing the trade-o between the percentage of correctly identi ed fraudsters versus the percentage of new subscribers raising alarms. We report here on a common suite of experiments we performed on these di erent sys-