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All Journal Jurnal CoreIT
Abdillah (Scopus ID: 57210600304), Rahmad
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Computer Science & IT

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Phishing Detection in Deep Learning: Systematic Literature Review Abdillah (Scopus ID: 57210600304), Rahmad; Syafitri, Wenni
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 10, No 1 (2024): June 2024
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v10i1.31009

Abstract

Abstract. Phishing is an attack that is harmful to organizations and individuals in cybersecurity. Many researchers use deep learning techniques to detect phishing. However, the proposed techniques still have shortcomings in terms of performance, especially in detecting unknown attacks, even though they have been developed in such a way. Therefore, to gain a more comprehensive understanding of the current state of research on the use of deep learning to detect phishing, a systematic literature review (SLR) is needed. This SLR aims to identify deep learning techniques, performance measures, overfitting techniques, datasets, parameters, phishing types, and recommendations for future phishing detection research. The method used by SLR consists of a research question and research objective, Search strategy, Inclusion and exclusion criteria, and Data extraction and Analysis. Over the past five years, SLR successfully identified 25 quality articles on phishing detection using deep learning. The contribution of this SLR is to provide insight into the current state of research and identify future research areas of phishing detection using deep learning techniques.
Co-Authors Wenni Syafitri, Wenni