SKIMA DL paper final.docx (3.66 MB)
Deep Learning with Convolutional Neural Network and Long Short-Term Memory for Phishing Detection
conference contribution
posted on 2023-08-30, 16:56 authored by Moruf A. Adebowale, Khin Lwin, Mohammed HossainPhishers sometimes exploit users’ trust of a known website’s appearance by using a similar page that looks like the legitimate site. In recent times, researchers have tried to identify and classify the issues that can contribute to the detection of phishing websites. This study focuses on design and development of a deep learning based phishing detection solution that leverages the Universal Resource Locator and website content such as images and frame elements. A Convolutional Neural Network (CNN) and the Long Short-Term Memory (LSTM) algorithm were used to build a classification model. The experimental results showed that the proposed model achieved an accuracy rate of 93.28%.
History
Page range
1-8ISSN
2573-3214External DOI
Publisher
IEEEPlace of publication
OnlineISBN
978-1-7281-2741-5Conference proceeding
2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)Name of event
2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)Location
Ulkulhas, MaldivesEvent start date
2019-08-26Event finish date
2019-08-28File version
- Accepted version
Language
- eng