Thèses en ligne de l'université 8 Mai 1945 Guelma

SIMBox Fraud Detection in Telecommunication Operators: A case Study on "Djezzy "

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dc.contributor.author BOUGUETTOUCHA, AHMED RAMI
dc.date.accessioned 2024-11-28T13:40:04Z
dc.date.available 2024-11-28T13:40:04Z
dc.date.issued 2024
dc.identifier.uri http://dspace.univ-guelma.dz/jspui/handle/123456789/16454
dc.description.abstract The SIMBox is a telecommunications device that reroutes international voice calls through the internet to a local SIM card within the device, making them appear as local calls and bypassing standard network gateways. This Master’s thesis presents a SIMBox Fraud Detector, an AI-powered web application for SIMBox fraud detec- tion in mobile telecommunications networks. A thorough experiments with machine learning techniques using the dataset CDR (Call Detail Records) from Djezzy mo- bile operator show that the XGBoost model with Tomek+RUS undersampling exhibits promising advantages in both detection and balance performance. XGBoost not only achieved a precision and accuracy of 96% for fraudulent detection, but it also pro- vided the best tradeoff between false positive rate and true positive rate. en_US
dc.language.iso en en_US
dc.publisher University of guelma en_US
dc.subject SIM Box Fraud, SIM Box Fraud Detection, Data Balancing, Call Detail Record, Machine Learning en_US
dc.title SIMBox Fraud Detection in Telecommunication Operators: A case Study on "Djezzy " en_US
dc.type Working Paper en_US


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