Frameworks For Fraud Detection In Mobile Telecommunications Networks
Peter Sherwood Burge, John S. Shawe-Taylor · 1996
Fraud is costing the mobile communications industry millions of pounds a year. A rapid solution is needed to reduce fraudulent activity in analogue networks and preventative measures are required to protect GSM and later UMTS. A joint European project `Advanced Security for Personal Communications Technologies ' (ASPeCT), part of the ACTS programme 1 , has been formed to research security issues in mobile communications networks. Part of this project is to investigate how Artificial Intelligence can be used by a network operator to detect fraudulent activity in a real-time environment. We discuss ways to characterize a user's behaviour by computing user profiles over sequences of Toll Tickets. We show that with a neural network fraud detection system we can monitor user behaviour patterns through both differential and absolute usage. A differential analysis enables us to detect changes in behaviour associated with a mobile telephone which could indicate fraudulent usage after a theft...