Phishing Detection Leveraging Machine Learning and Deep Learning: A Review
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Abstract (arXiv)
Phishing attacks trick victims into disclosing sensitive information. To counter rapidly evolving attacks, we must explore machine learning and deep learning models leveraging large-scale data. We discuss models built on different kinds of data, along with their advantages and disadvantages, and present multiple deployment options to detect phishing attacks.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 May 2022.
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Citing papers per year: 2024: 3.
3 papers.
- 2024KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detectioncited by 29
- 2024Novel Interpretable and Robust Web-based AI Platform for Phishing Email Detectioncited by 7
- 2024Multimodal Large Language Models for Phishing Webpage Detection and Identificationcited by 6
- 2024Multimodal Large Language Models for Phishing Webpage Detection and Identification12 Aug 2024
- 2024Novel Interpretable and Robust Web-based AI Platform for Phishing Email Detection19 May 2024
- 2024KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detection4 Mar 2024