Online Recruitment Fraud Detection

Author(s)	Ms. Mahima Nanasaheb Nawale, Dr. P. S. Gholap, Dr. S. S. Khatal, Minal Goraksh Tattu, Vivek Sanjay Maval
Country	India
Abstract	This research proposes an Online Recruitment Fraud Detection System that identifies fake job advertisements using machine learning and rule-based techniques. The system preprocesses job descriptions and applies TF-IDF for feature extraction. A Logistic Regression model is used to classify job postings as real or fraudulent. Additionally, rule-based filtering detects suspicious patterns such as unrealistic salaries and fake company details. The hybrid approach improves detection accuracy and helps protect job seekers from recruitment scams.
Keywords	Online Recruitment Fraud Detection, Machine Learning, TF-IDF, Logistic Regression, Natural Language Processing, Cybersecurity
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-04-03

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