Open AccessBidirectional Artificial Neural Networks for Mobile‐Phone Fraud Detection
Author(s) -
Krenker Andrej,
Volk Mojca,
Sedlar Urban,
Bešter Janez,
Kos Andrej
Publication year - 2009
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.09.0208.0245
Subject(s) - mobile phone , artificial neural network , computer science , key (lock) , phone , call duration , core network , real time computing , artificial intelligence , telecommunications , computer security , linguistics , philosophy
We propose a system for mobile‐phone fraud detection based on a bidirectional artificial neural network (bi‐ANN). The key advantage of such a system is the ability to detect fraud not only by offline processing of call detail records (CDR), but also in real time. The core of the system is a bi‐ANN that predicts the behavior of individual mobile‐phone users. We determined that the bi‐ANN is capable of predicting complex time series (Call_Duration parameter) that are stored in the CDR.