SMARTPROFILENET: CNN-DRIVEN SYSTEM FOR IDENTIFYING FRAUDULENT USER PROFILES

Abstract

The rapid growth of online platforms has led to a surge in fraudulent user profiles, compromising data integrity and user trust. Traditional fraud detection systems often rely on rule-based or manual inspection methods, which are unable to adapt to evolving fraudulent patterns. This paper presents SmartProfileNet, a deep learning framework that leverages Convolutional Neural Networks (CNNs) to automatically detect fraudulent profiles. The proposed system analyzes user behavior, profile attributes, and interaction patterns to identify suspicious accounts. Experimental evaluations demonstrate that SmartProfileNet achieves high accuracy and robustness compared to conventional methods, making it a reliable solution for large-scale online platforms.