Email spam: A comprehensive review of optimize detection methods, challenges, and open research problems

EH Tusher, MA Ismail, MA Rahman, AH Alenezi… - IEEE …, 2024 - ieeexplore.ieee.org
Nowadays, emails are used across almost every field, spanning from business to education.
Broadly, emails can be categorized as either ham or spam. Email spam, also known as junk …

[HTML][HTML] A Systematic Review of Deep Learning Techniques for Phishing Email Detection

PH Kyaw, J Gutierrez, A Ghobakhlou - Electronics, 2024 - mdpi.com
The landscape of phishing email threats is continually evolving nowadays, making it
challenging to combat effectively with traditional methods even with carrier-grade spam …

Phishing email detection model using deep learning

S Atawneh, H Aljehani - Electronics, 2023 - mdpi.com
Email phishing is a widespread cyber threat that can result in the theft of sensitive
information and financial loss. It uses malicious emails to trick recipients into providing …

Advancing Phishing Email Detection: A Comparative Study of Deep Learning Models

N Altwaijry, I Al-Turaiki, R Alotaibi, F Alakeel - Sensors, 2024 - mdpi.com
Phishing is one of the most dangerous attacks targeting individuals, organizations, and
nations. Although many traditional methods for email phishing detection exist, there is a …

Evaluating the performance of chatgpt for spam email detection

S Si, Y Wu, L Tang, Y Zhang, J Wosik - arXiv preprint arXiv:2402.15537, 2024 - arxiv.org
Email continues to be a pivotal and extensively utilized communication medium within
professional and commercial domains. Nonetheless, the prevalence of spam emails poses a …

An Improved Dandelion Optimizer Algorithm for Spam Detection: Next-Generation Email Filtering System

M Tubishat, F Al-Obeidat, AS Sadiq, S Mirjalili - Computers, 2023 - mdpi.com
Spam emails have become a pervasive issue in recent years, as internet users receive
increasing amounts of unwanted or fake emails. To combat this issue, automatic spam …

[HTML][HTML] MIDAS: Multi-layered attack detection architecture with decision optimisation

K Rendall, A Mylonas, S Vidalis, D Gritzalis - Computers & Security, 2025 - Elsevier
The proliferation of cyber attacks has led to the use of data-driven detection
countermeasures, in an effort to mitigate this threat. Machine learning techniques, such as …

DeepEPhishNet: a deep learning framework for email phishing detection using word embedding algorithms

M Somesha, AR Pais - Sādhanā, 2024 - Springer
Email phishing is a social engineering scheme that uses spoofed emails intended to trick the
user into disclosing legitimate business and personal credentials. Many phishing email …

SpearBot: Leveraging Large Language Models in a Generative-Critique Framework for Spear-Phishing Email Generation

Q Qi, Y Luo, Y Xu, W Guo, Y Fang - arXiv preprint arXiv:2412.11109, 2024 - arxiv.org
Large Language Models (LLMs) are increasingly capable, aiding in tasks such as content
generation, yet they also pose risks, particularly in generating harmful spear-phishing …

Adapting to Cyber Threats: A Phishing Evolution Network (PEN) Framework for Phishing Generation and Analyzing Evolution Patterns using Large Language Models

F Chen, T Wu, V Nguyen, S Wang, H Hu… - arXiv preprint arXiv …, 2024 - arxiv.org
Phishing remains a pervasive cyber threat, as attackers craft deceptive emails to lure victims
into revealing sensitive information. While Artificial Intelligence (AI), particularly deep …