Online Recruitment Fraud Detection Using Deep Learning Approaches

Author(s)	Ms. Kallem Sheshma, Ms. Gunnala Varshitha, Ms. Kadam Sowmya, Ms. Kemidi Sowmya, Prof. R.A. Manikandan
Country	India
Abstract	With the growth of online recruitment platforms like LinkedIn and Indeed, job searching has become easier and more accessible. However, these platforms are also increasingly targeted by cybercriminals who post fake job advertisements to deceive job seekers. This type of cybercrime, known as Online Recruitment Fraud (ORF), can lead to financial loss and identity theft. Recent advances in Natural Language Processing using transformer models such as BERT and RoBERTa provide effective ways to analyze job descriptions and detect fraudulent postings automatically.
Keywords	Online Recruitment Fraud, BERT, RoBERTa, CNN2D, SMOTE, Natural Language Processing, Fraud Detection.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-04-16
DOI	https://doi.org/10.36948/ijfmr.2026.v08i02.71264

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