Fraud Detection in Mobile Payments Utilizing Process Behavior Analysis
Generally, fraud risk implies any intentional deception made for financial gain. In this paper, the authors consider this risk in the field of services which support transactions with electronic money. Specifically, they apply a tool for predictive security analysis at runtime which observes process behavior with respect to transactions within a money transfer service and tries to match it with expected behavior given by a process model. They analyze deviations from the given behavior specification for anomalies that indicate a possible misuse of the service related to money laundering activities. They evaluate the applicability of the proposed approach and provide measurements on computational and recognition performance of the tool - Predictive Security Analyzer - produced using real operational and simulated logs.