Fake Social Media Profile Detection and Reporting

In the age of technology, social media has become a part of communication, business, and public interaction. Nevertheless, the increasing number of fake profiles on social media platforms such as Instagram has resulted in major problems such as misinformation, scam engagements, impersonation, and decreased trust. This paper suggests an end-to-end solution for identifying and reporting fake social media profiles based on machine learning coupled with blockchain technology. The system is called Ghost Block, and it offers a hybrid log mechanism built with Web2 and Web3. Besides this, the log-in mechanism has an ML model that is trained on profile features: the count of followers/following, engagement rate, and completeness of the profile of an Instagram account to predict the authenticity. Blockchain is also integrated for verifiable and tamper-proof logging of detection outcomes through MetaMask. The application is deployed using modern full-stack tools and provides a responsive interface with explainable AI support. The model showed great performance with an accuracy of over 94% and is ready for real-world use by individuals, businesses, and digital auditors.