Application of Association Rules in Telecommunication Network Fraud Cases

Abstract

As a new form of fraud, telecom network fraud is characterized by remoteness and contactless. After collecting reports of telecom network fraud cases through the Internet and simulating the case datasets based on the report findings, this paper selects the datasets related to characteristics of the suspects for pre-processing and transformation, applies the association rule algorithm to telecom network fraud cases, and uses Apriori algorithm and FP-Growth algorithm to mine the valuable information of the characteristics of the suspects involved in telecom network fraud cases. By doing so, this paper discovers the association relationship between the characteristics of the suspects, and proposes relevant prevention suggestions on this basis to help combat telecom network fraud crimes. CCS concept •Computing methodologies∼Machine learning∼Machine learning approaches∼Rule learning