Online Recruitment Fraud Detection Using Machine Learning

Online Recruitment Fraud Detection Using Machine Learning

Dr.PSV. Srinivasa Rao1, A.Prem kumar2, Anas Abdullah3 ,Ch.Rajeshwari4 ,K.devika5
1Dr.PSV.Srinivasa Rao (professor)

2A.Prem Kumar Department of Computer Science and Engineering (Joginpally b.r. Engineering College) 3Anas Abdullah Department of Computer Science and Engineering (Joginpally b.r. Engineering College) 4Ch.Rajeshwari Department of Computer Science and Engineering (Joginpally b.r. Engineering College) 5K.Devika Department of Computer Science and Engineering (Joginpally b.r. Engineering College)

Abstract - The research suggests using machine learning classification methods to identify and prevent fake job postings  online.  Nowadays,  many  companies  prefer  to

advertise their job vacancies on the internet for easy access by job seekers. However, there are scammers who trick people into paying for non-existent jobs. Through data analysis and machine learning, we can distinguish between legitimate and fake job postings. Various algorithms are utilized to detect fraudulent posts and protect job seekers from falling victim to scams. The system is designed to teach the model how to distinguish between real and fake job listings using past data on fraudulent and legitimate job postings. Initially, supervised learning algorithms like classification techniques can be used to tackle the problem of identifying scammers in job ads. It will utilize multiple machine learning algorithms and choose the one with the best accuracy in predicting if a job posting is legitimate or not.

Key Words: Fraud Job, Job Seeker, Machine Learning, Internet Recruitment, Classification