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Hybrid Deep Learning Approaches Enable Intrusion Detection System for Zero-Day Phishing Detection

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Published in:VFAST Transactions on Software Engineering
Format: Online Article RSS Article
Published: 2025
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container_title VFAST Transactions on Software Engineering
description
discipline_display Technology & Engineering
discipline_facet Technology & Engineering
format Online Article
RSS Article
genre Journal Article
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institution FRELIP
journal_source_facet VFAST Transactions on Software Engineering
publishDate 2025
publishDateSort 2025
record_format rss_article
spellingShingle Hybrid Deep Learning Approaches Enable Intrusion Detection System for Zero-Day Phishing Detection
Software
Technology & Engineering — Computing
Technology & Engineering
sub_discipline_display Technology & Engineering — Computing
sub_discipline_facet Technology & Engineering — Computing
subject_display Software
Technology & Engineering — Computing
Technology & Engineering
Software
Technology & Engineering — Computing
Technology & Engineering
subject_facet Software
Technology & Engineering — Computing
Technology & Engineering
title Hybrid Deep Learning Approaches Enable Intrusion Detection System for Zero-Day Phishing Detection
title_auth Hybrid Deep Learning Approaches Enable Intrusion Detection System for Zero-Day Phishing Detection
title_full Hybrid Deep Learning Approaches Enable Intrusion Detection System for Zero-Day Phishing Detection
title_fullStr Hybrid Deep Learning Approaches Enable Intrusion Detection System for Zero-Day Phishing Detection
title_full_unstemmed Hybrid Deep Learning Approaches Enable Intrusion Detection System for Zero-Day Phishing Detection
title_short Hybrid Deep Learning Approaches Enable Intrusion Detection System for Zero-Day Phishing Detection
title_sort hybrid deep learning approaches enable intrusion detection system for zero-day phishing detection
topic Software
Technology & Engineering — Computing
Technology & Engineering
url https://vfast.org/journals/index.php/VTSE/article/view/2287