A genetic programming approach to telecommunications fraud detection and classification

Abstract

Telecommunications fraud has drawn the researchers’ attention due to the huge economic burden on companies and to the interesting aspect of users’ behavior modeling. In the present paper, an application of genetic programming to fraud detection is presented. Genetic programming is used for case classification in order to distinguish between normal and fraudulent activities in a telecommunications network. Implications to appropriate user behavior modeling are, also, discussed. Real world cases of defrauded user accounts are modeled by means of selected usage features and comparisons with other approaches are made.