Deep Learning Approach For Detecting Fake Job Posting In Online Recruitment Platform

• Author(s):

  Mrs.N.Sathiya Rani | M.Jeyakumar | B.Bala

• Keywords:

  Fake Job Detection, Machine Learning, Web Scraping, Natural Language Processing, Ensemble Classification, Cyber Security, Semantic Analysis

• Abstract:

  The Rapid Growth Of Online Job Portals Has Changedhow People Find Work, Making The Process Much Easier. However, This Easy Access Has Also Led To A Massive Increase In Fake Job Postings And Employment Scams. Scammers Use These Platforms To Steal Personal Information And Trick Vulnerable Applicants Out Of Their Money. This Paper Proposes An Automated System To Detect And Identify Fake Job Ads On Popular Platforms Like LinkedIn, Naukri, Indeed, And Internshala. The System Uses Web Scraping Tools To Collect Live Job Data Directly From The Internet. Natural Language Processing (NLP) Techniques Are Then Used To Clean The Text And Find Suspicious Words Or Phrases. Finally, A Machine Learning (ML) Model Looks At These Features To Decide Whether The Job Is Real Or Fake. By Using This Automated Check, The System Gives Users A Safe And Highly Reliable Way To Verify Job Offers. Testing Shows That The System Can Successfully Catch Scams With Excellent Accuracy.

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Other Details

• Paper id:

  IJSARTV12I3104744

• Published in:

  Volume: 12 Issue: 3 March 2026

• Publication Date:

  2026-03-19

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