EXPOSING ONLINE RECRUITMENT FRAUD WITH DEEP LEARNING ALGORITHMS

Abstract

The problem of fraudulent recruitment is a significant problem with the internet job market. others engage in this practice when they make an effort to deceive others who are looking for work by presenting them with phony job offers and money transactions. With the help of deep learning algorithms, our research intends to put an end to these fraudulent practices by evaluating job advertisements, emails, and application procedures. Through the utilization of Natural Language Processing (NLP) in conjunction with more sophisticated models like LSTM and BERT, the system is able to identify irregularities and alert users to the possibility of being taken advantage of. The findings indicate that solutions that are powered by artificial intelligence have the potential to lessen the risks that are associated with the recruitment process, protect job seekers, and preserve the integrity of online applicant tracking systems.