Fake Job Defection System Using Llama-3 and Machine Learning

With the evolution of online recruiting websites, fake job postings have become rampant leading to money extortion and cyber-crimes. Traditional methods for the detection of fake job postings are unable to recognize any semantic and hidden patterns in frauds. In this paper, a smart Fake Job Detection System has been proposed using the LLaMA-3 large language model in combination with the Machine Learning algorithms and NLP techniques. This system will detect fraudulent jobs by analyzing details like the description of the job, recruiter details, company details, salary offered. The framework has been implemented and experimentally analysed.