Fake Account Detection Using ANN Based Model in Machine Learning
Y. Alekya Rani, Ganja Srividya, Allam Balaram, Kotha Harish Kumar, Ajmeera Kiran, Manda Silparaj
Abstract
In the digital age, the proliferation of fake accounts on various platforms poses significant challenges in terms of cybersecurity, misinformation, and online harassment. To combat this issue, this project aims to develop a robust fake account detection system using machine learning techniques. The project involves the collection of user data, feature engineering,data preprocessing, and the selection of suitable machine learning algorithms. The model is trained and evaluated using relevant metrics to distinguish between real and fake accounts effectively. Once deployed, this system continuously monitors user activities and alerts administrators when fake accounts are detected, enabling timely and legal compliance. The success of this project depends on the quality and quantity of data as well as the ability to adapt and improve the detection methods over time, in a constant battle against evolving fake account creation techniques.