Privacy-Preserving Fraud Detection Across Multiple Phone Record Databases

Subscription fraud, i.e., customers signing up to a service with no intent to pay, causes significant losses in the telecommunication industry. Telecom operators have developed strategies to identify those fraudsters, but fraudsters tend to migrate from one carrier to another. Data sharing between telecoms would increase fraud detection rates, but phone records are protected by law and telecom operators might be reluctant to share information about fraudsters because they see it as giving a competitive advantage. We propose several protocols to enable fraud detection across multiple databases without revealing additional information. We also propose a model to generate phone records, with which we evaluate how the choice of parameters affects detection performance. We show feasibility, performance and costs with implementations of our protocols.

1 Introduction

Fraud—the deliberate practice of deception in order to secure unfair or unlawful gain—is as old as humanity itself and is quick to adapt to new technologies.