Application of word embedding and machine learning in detecting phishing websites

Routhu Srinivasa Rao (), Amey Umarekar () and Alwyn Roshan Pais ()
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Routhu Srinivasa Rao: GMR Institute of Technology
Amey Umarekar: National Institute of Technology
Alwyn Roshan Pais: National Institute of Technology

Telecommunication Systems: Modelling, Analysis, Design and Management, 2022, vol. 79, issue 1, No 4, 33-45

Abstract: Abstract Phishing is an attack whose aim is to gain personal information such as passwords, credit card details etc. from online users by deceiving them through fake websites, emails or any legitimate internet service. There exists many techniques to detect phishing sites such as third-party based techniques, source code based methods and URL based methods but still users are getting trapped into revealing their sensitive information. In this paper, we propose a new technique which detects phishing sites with word embeddings using plain text and domain specific text extracted from the source code. We applied various word embedding for the evaluation of our model using ensemble and multimodal approaches. From the experimental evaluation, we observed that multimodal with domain specific text achieved a significant accuracy of 99.34% with TPR of 99.59%, FPR of 0.93%, and MCC of 98.68%

Keywords: URL; Phishing; Anti-phishing; TF-IDF; Hostname; Random forest (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11235-021-00850-6

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