A systematic literature review on phishing email detection using natural language processing techniques

S Salloum, T Gaber, S Vadera, K Shaalan - IEEE Access, 2022 - ieeexplore.ieee.org
Every year, phishing results in losses of billions of dollars and is a major threat to the Internet
economy. Phishing attacks are now most often carried out by email. To better comprehend …

Applications of deep learning for phishing detection: a systematic literature review

C Catal, G Giray, B Tekinerdogan, S Kumar… - … and Information Systems, 2022 - Springer
Phishing attacks aim to steal confidential information using sophisticated methods,
techniques, and tools such as phishing through content injection, social engineering, online …

Phishing or not phishing? A survey on the detection of phishing websites

R Zieni, L Massari, MC Calzarossa - IEEE Access, 2023 - ieeexplore.ieee.org
Phishing is a security threat with serious effects on individuals as well as on the targeted
brands. Although this threat has been around for quite a long time, it is still very active and …

A hybrid DNN–LSTM model for detecting phishing URLs

A Ozcan, C Catal, E Donmez, B Senturk - Neural Computing and …, 2023 - Springer
Phishing is an attack targeting to imitate the official websites of corporations such as banks,
e-commerce, financial institutions, and governmental institutions. Phishing websites aim to …

Phishing attacks detection using deep learning approach

I Saha, D Sarma, RJ Chakma, MN Alam… - … on Smart Systems …, 2020 - ieeexplore.ieee.org
In the COVID-19 pandemic, people are enforced to adopt 'work from home'policy. The
Internet has become an effective channel for social interactions nowadays. Peoples' …

An improved ELM-based and data preprocessing integrated approach for phishing detection considering comprehensive features

L Yang, J Zhang, X Wang, Z Li, Z Li, Y He - Expert Systems with …, 2021 - Elsevier
In this paper, a novel approach based on non-inverse matrix online sequence extreme
learning machine (NIOSELM) for phishing detection is presented, which takes into account …

GramBeddings: a new neural network for URL based identification of phishing web pages through n-gram embeddings

AS Bozkir, FC Dalgic, M Aydos - Computers & Security, 2023 - Elsevier
There has been ever-growing use of Internet and progress within many communication
channels such as social media and this escalates the need for rapid and low source …

Prompt engineering or fine-tuning? a case study on phishing detection with large language models

F Trad, A Chehab - Machine Learning and Knowledge Extraction, 2024 - mdpi.com
Large Language Models (LLMs) are reshaping the landscape of Machine Learning (ML)
application development. The emergence of versatile LLMs capable of undertaking a wide …

Awareness model for minimizing the effects of social engineering attacks in web applications

M Al-Khateeb, M Al-Mousa… - … Journal of Data and …, 2023 - growingscience.com
Social Engineering (SE) Attacks against information systems continue to pose a potentially
devastating impact. Security information systems are becoming increasingly significant as …

Anti-phishing: A comprehensive perspective

G Varshney, R Kumawat, V Varadharajan… - Expert Systems with …, 2024 - Elsevier
Phishing is a form of deception technique that attackers often use to acquire sensitive
information related to individuals and organizations fraudulently. Although Phishing attacks …