Detection And Classification Of Bypass (Simbox) Fraud Using Deep Learning: The Case Of Ethio Telecom

Abstract

Telecom Frauds Are A Major Problem That Affects Operators And Telecoms Organizations All Around The World. Fraudsters Have Used Technological Advancements In The Organization To Their Advantage To Commit Fraud. Simbox/Bypass Fraud Is One Of The Most Common Types Of Telecomfraud, And It Involves The Use Of Voice Over IP (Voip) Technologies To Avoid Access Charges And Profit On International Calls. Due To The Dynamic Nature Of This Fraud, It Can Quickly Defeat The Test Call Generators (TCG) And FMS (Fraud Management System). In Addition To TCG And FMS Near Real-Time Machine Learning Approach Has Been Designed To Detect And Classify Simbox/Bypass Fraud Which Required Uptodate Data A Problem And Supervised Machine Learning Algorithms Show Limitations To Capture The Dynamic Nature Of Fraud. To Detect And Classify Simbox/Bypass Fraud, Deep Learning/Deep Neural Network Classifier Algorithms Were Used In This Study, Namely MLP (Multilayer Perceptron), RNN (Recurrent Neural Network), And LSTM (Long Short-Term Memory), With The Two Validation Techniques 10-Fold Cross-Validation And Separate Train Test. After Collecting Call Detail Record (CDR) Data From Ethio Telecom, Relevant Features Were Chosen And Preparation Operations Such As Data Cleaning, Integrating, And Aggregating Were Completed. Theexperimental Results Demonstrate That MLP (Multilayer Perceptron) Classifier With A Separate Test Data Validation Technique Obtains A Higher Classification Accuracy (99.17%), LSTM (Long Short Term Memory) Is Ranked Second With An Overall Performance Accuracy Of 98.90%, And RNN(Recurrent Neural Network) Is Ranked Third With An Accuracy Of 98.10%. Detecting And Classifying Simbox/Bypass Fraud Has Numerous Advantages For Telecom Companies, Including Raising Awareness To Mitigate Risk, Preventing Financial Loss, Increasing Revenue Assurance, Improving Operational Efficiency, Improving Customer Satisfaction, Protecting Brand Reputation, Ensuring Regulatory Compliance, And Establishing Industry Leadership.