Fake profile Identification

Abstract

The explosive growth of social platforms like Facebook and Twitter as well as fake profile presence has become an urgent problem that endangers user confidentiality and security and digital confidence. The current approaches to detect fake profiles through manual verification and rule based algorithms fail because they lack the necessary scalability and accuracy as well as adaptability to newer deceitful methods. The proposed NN based solution automatically identifies fake profiles with outstanding precision levels. The system uses genuine and fabricated user profile data to train itself with the important traits including account age and friend count and activity level functions. The Python development through TensorFlow and Keras and Pandas libraries creates a system which integrates a friendly user interface through Tkinter for delivering accurate results alongside operational scalability and efficiency. The proposed system both operates system automation for detection tasks alongside resolved previous limitations to enable better security solutions for online social platforms in real time.