Secure & Reliable Fake Profile Detection on Recruitment Platforms using Machine Learning and Blockchain
Soumya Pokharna, Palash Sharma, Tanushree Taneja, Saurav Verma, Harsh Ojha · Procedia Computer Science · 2025
Professional networking sites like LinkedIn have made the hiring process “falser” in the context of several "duplicate" profiles; therefore, attempts are being made to change this area by using blockchain technology and machine learning for the dual-validation system of the profile authenticity. Then, for this purpose, a user interface based on a browser extension is developed such that it becomes very easy for recruiters to interface with it. The blockchain technology authenticates certification credentials, and AI/ML models analyze LinkedIn profile data to validate whether it is a genuine or fake profile based on pre-trained criteria. By leveraging blockchain’s immutable nature, credential authenticity is safeguarded, ensuring that once verified, certifications cannot be tampered with. Meanwhile, machine learning models continuously analyze behavioral data such as abnormal connection growth and unusual activity patterns to detect signs of fraudulent profiles.