Enhancing Online Job Posting Security: A Big Data Approach to Fraud Detection

In the digital era, online employment platforms have revolutionized the hiring landscape, offering unprecedented convenience and accessibility to both employers and job seekers. Nevertheless, this newfound ease has attracted malicious entities seeking to exploit the system through the dissemination of deceptive job listings. These fraudulent activities pose significant threats to businesses and individuals, encompassing financial losses, damage to reputation, and potential legal ramifications. This study leverages Apache Spark and Big Data to develop an advanced fraud detection system for online job postings. Our primary objective is to enhance the precision and efficiency of detecting and preventing fraudulent job advertisements. This will be achieved through the comprehensive analysis and processing of vast datasets extracted from various employment websites. By harnessing the power of these cutting-edge technologies, our investigation aims to fortify the integrity of online employment platforms, safeguarding the interests of both employers and job seekers alike.