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Detecting advance fee fraud using NLP bag of word model

Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
 Peer-review

Abstract

Advance Fee Fraud (AFF) is a form of Internet fraud prevalent within the Cybercrimes domain in literature. Evidence shows that huge financial assets are stolen from the global economy as a result of AFF. Consequently, this paper presents a fraudulent email classifier (FEC) that detects and classifies an email as fraudulent or non-fraudulent using Natural Language Process (NLP) model referred to as Bag-of-Words (BoW). The classifier is designed and trained to detect and classify AFF that originate from known sources using Nigeria as a Case study. Dataset is obtained and used for the training while testing the classifier logs. Experimentally, the classifier was trained using various machine learning algorithms with BoW generated as predictors. By selecting the best algorithms, the classifier was tested and found to perform satisfactorily.

Publication Information

Output type

Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
 Peer-review

Original language

English

Article number

9428793

Pages from-to (Number of pages)

Pages 94-97 (4 pages)

Publication milestones

  • Published - 25/05/2021

Publication status

Published - 25/05/2021

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

Publication series

  • Publication series name: Proceedings of the 2020 IEEE 2nd International Conference on Cyberspace, CYBER NIGERIA 2020

ISBN (Print)

9781665444095

ISBN (Electronic)

9781665444095

Publication IDs

  • handle.net: 10547/625056
  • Scopus: 85107509292

Host publication title

Proceedings of the 2020 IEEE 2nd International Conference on Cyberspace, CYBER NIGERIA 2020

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