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Erschienen in:
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2024 | OriginalPaper | Buchkapitel

Phishing Classification Based on Text Content of an Email Body Using Transformers

verfasst von : M. Somesha, Alwyn R. Pais

Erschienen in: Information Security, Privacy and Digital Forensics

Verlag: Springer Nature Singapore

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Abstract

Phishing attacks steal sensitive credentials using different techniques, tools, and some sophisticated methods. The techniques include content injection, information re-routing, social engineering, server hacking, social networking, SMS and WhatsApp mobile applications. To overcome such attacks and minimize risks of such attacks, many phishing detection and avoidance techniques were introduced. Among various techniques, deep learning algorithms achieved the efficient results. In the proposed work, a transformers-based technique is used to classify phishing emails. The proposed method outperformed the other similar mechanisms for the classification of phishing emails. The phishing classification accuracy achieved by the proposed work is 99.51% using open-source datasets. The proposed model is also used to learn and validate the correctness of the in-house created datasets. The obtained results with in-house datasets are equally competitive.

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Vorheriges Kapitel Forensics Analysis of TOR Browser
Nächstes Kapitel Vehicle Theft Detection and Tracking Using Surveillance Video for the Modern Traffic Security Management System
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Metadaten
Titel
Phishing Classification Based on Text Content of an Email Body Using Transformers
verfasst von
M. Somesha
Alwyn R. Pais
Copyright-Jahr
2024
Verlag
Springer Nature Singapore
Buch
Information Security, Privacy and Digital Forensics

Print ISBN: 978-981-9950-90-4

Electronic ISBN: 978-981-9950-91-1

Copyright-Jahr: 2024

DOI
https://doi.org/10.1007/978-981-99-5091-1_25

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