📄 Abstract
Social media has completely changed the way we communicate, connect with others, and share our lives online. Among the many platforms available today, Instagram stands out as one of the most widely used, with millions of people sharing photos, videos, and personal moments every day. But this popularity comes with a downside — the platform has also seen a sharp rise in fake profiles, which pose real risks to user security and privacy. These fake accounts are often behind impersonation, online scams, the spread of misinformation, and various other harmful activities. Right now, most platforms rely on manual verification and user reporting to catch fake profiles. The problem is, this approach is slow, labour-intensive, and often struggles to keep up with increasingly sophisticated fake accounts. What's really needed is a smarter, automated system that can detect these profiles more accurately and efficiently. That's exactly what this project sets out to do. "AI-Based Fake Profile Detection for Instagram Using Machine Learning" is a system designed to spot suspicious Instagram accounts using AI and machine learning techniques. It works by examining key features from a user's profile, pulling out the most relevant characteristics, and running them through a trained machine learning model that classifies the account as either genuine or fake. The system is built using Python and the Flask framework, along with various machine learning libraries. It comes with a simple, easy-to-use interface where users can input profile details and instantly get a prediction. Beyond just labeling a profile as real or fake, the system also provides a confidence score, a risk level, and a brief explanation — all aimed at helping users better understand and trust the results. By automating this process, the system significantly cuts down on the need for manual checks and offers a much faster way to flag potentially fake accounts. It's a practical example of how artificial intelligence can be applied to real-world cybersecurity and social media safety challenges. Looking ahead, there's plenty of room to build on this work — for instance, by incorporating deep learning for image analysis, natural language processing for text-based cues, real-time data analysis, and more advanced behavioural detection techniques.
📚 How to Cite:
G. Vennela Vijaya Lakshmi, V. Gulabi, Y. Shoba, D. Aruna Padma, V. Sailaja, K. Leela Pavani, Sunil B, B. Jyothi , AI BASED FAKE PROFILE DETECTION SYSTEM FOR INSTAGRAM USING MACHINE LEARNING , Volume 12 , Issue 7, July 2026, EPRA International Journal of Multidisciplinary Research (IJMR) , Pages: 863 - 869 ,