Comparative Analysis of Machine Learning Algorithms for Email Phishing Detection Using TF-IDF, Word2...
Comparative Analysis of Machine Learning Algorithms for Email Phishing Detection Using TF-IDF, Word2Vec, and BERT
About this item
Full title
Author / Creator
Publisher
Henderson: Tech Science Press
Journal title
Language
English
Formats
Publication information
Publisher
Henderson: Tech Science Press
Subjects
More information
Scope and Contents
Contents
Cybercriminals often use fraudulent emails and fictitious email accounts to deceive individuals into disclosing confidential information, a practice known as phishing. This study utilizes three distinct methodologies, Term Frequency-Inverse Document Frequency, Word2Vec, and Bidirectional Encoder Representations from Transformers, to evaluate the ef...
Alternative Titles
Full title
Comparative Analysis of Machine Learning Algorithms for Email Phishing Detection Using TF-IDF, Word2Vec, and BERT
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_3199833890
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3199833890
Other Identifiers
ISSN
1546-2226,1546-2218
E-ISSN
1546-2226
DOI
10.32604/cmc.2024.057279
