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dc.contributor.authorHamisu, Muhammad
dc.contributor.authorMansour, Ali
dc.date.accessioned2021-07-19T10:49:19Z
dc.date.available2021-07-19T10:49:19Z
dc.date.issued2021-05-25
dc.identifier.citationHamisu M, Mansour A (2021) 'Detecting advance fee fraud using NLP bag of word model', 2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA) - Abuja, Institute of Electrical and Electronics Engineers Inc..en_US
dc.identifier.isbn9781665444095
dc.identifier.doi10.1109/CYBERNIGERIA51635.2021.9428793
dc.identifier.urihttp://hdl.handle.net/10547/625056
dc.description.abstractAdvance 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.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.urlhttps://ieeexplore.ieee.org/document/9428793en_US
dc.subjectAdvance Fee Frauden_US
dc.subjectInternet frauden_US
dc.subjectmachine learning Bag-of-Wordsen_US
dc.titleDetecting advance fee fraud using NLP bag of word modelen_US
dc.typeConference papers, meetings and proceedingsen_US
dc.contributor.departmentUniversity of Bedfordshireen_US
dc.date.updated2021-07-19T10:47:14Z
dc.description.note


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