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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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