Tresorlarry/phishing-detector-cameroon

AI-Based Phishing Detection for Financial Transaction Fraud Prevention in Cameroon # phishing-detector-cameroon AI-Based Phishing Detection System for Financial Transaction Fraud Prevention in Cameroon Case Study: MTN Mobile Money and Orange Money Overview Financial technology has transformed digital payments and money transfer services in Cameroon. Platforms such as MTN Group Mobile Money and Orange S.A. Orange Money have significantly improved access to financial services, especially for individuals without traditional banking access. However, the rapid growth of mobile financial transactions has also increased the prevalence of cyber fraud and phishing attacks targeting users. This project presents the Design and Implementation of an AI-Based Phishing Detection System for Financial Transaction Fraud Prevention in Cameroon, focusing on the local context and challenges affecting users of MTN Mobile Money and Orange Money. The system applies Artificial Intelligence and Machine Learning techniques to detect suspicious patterns, fraudulent SMS messages, phishing links, and transaction behaviors that may indicate fraud attempts. The study is motivated by the increasing reports of financial scams in Cameroon, including fake promotional messages, account verification scams, social engineering attacks, and unauthorized transaction attempts. Problem Statement Cameroon has experienced a rise in mobile money adoption alongside increasing cyber-enabled financial fraud. Fraudsters exploit weaknesses in user awareness and communication channels through phishing messages and deceptive transaction requests. Common attacks include: • Fake MTN or Orange promotional messages • Fraudulent account verification requests • Fake customer service communications • SMS and URL phishing attacks • Social engineering scams • Unauthorized transaction prompts Current prevention methods rely heavily on manual reporting and user vigilance, creating a need for intelligent automated fraud detection systems capable of identifying threats in real time. Research Aim To des …