Cover Image

The Performance of Sequential Deep Learning Models in Detecting Phishing Websites Using Contextual Features of URLs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gopali, Saroj, Namin, Akbar S., Abri, Faranak, Jones, Keith S.
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PhishGuard: A Convolutional Neural Network Based Model for Detecting Phishing URLs with Explainability Analysis
by: Islam, Md Robiul, et al.
Published: (2024)

PhishNet: A Phishing Website Detection Tool using XGBoost
by: Kumar, Prashant, et al.
Published: (2024)

Automated Phishing Detection Using URLs and Webpages
by: Wang, Huilin, et al.
Published: (2024)

The Application of Transformer-Based Models for Predicting Consequences of Cyber Attacks
by: Chhetri, Bipin, et al.
Published: (2025)

The Performance of the LSTM-based Code Generated by Large Language Models (LLMs) in Forecasting Time Series Data
by: Gopali, Saroj, et al.
Published: (2024)

IoT Malware Network Traffic Detection using Deep Learning and GraphSAGE Models
by: Prajapati, Nikesh, et al.
Published: (2025)

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features
by: Faisal, Aseer Al
Published: (2025)

PhishVQC: Optimizing Phishing URL Detection with Correlation Based Feature Selection and Variational Quantum Classifier
by: Shahriyar, Md. Farhan, et al.
Published: (2025)

PhreshPhish: A Real-World, High-Quality, Large-Scale Phishing Website Dataset and Benchmark
by: Dalton, Thomas, et al.
Published: (2025)

NoPhish: Efficient Chrome Extension for Phishing Detection Using Machine Learning Techniques
by: Thaqi, Leand, et al.
Published: (2024)

AntiPhishStack: LSTM-based Stacked Generalization Model for Optimized Phishing URL Detection
by: Aslam, Saba, et al.
Published: (2024)

A Lightweight Hybrid MLP-Based Framework for Real-Time Phishing URL Detection Using Structural URL Features
by: Emmanuel, Uche Unoke, et al.
Published: (2026)

PhishSSL: Self-Supervised Contrastive Learning for Phishing Website Detection
by: Li, Wenhao, et al.
Published: (2025)

Fishing for Phishers: Learning-Based Phishing Detection in Ethereum Transactions
by: Alghuried, Ahod, et al.
Published: (2025)

Prompted Contextual Vectors for Spear-Phishing Detection
by: Nahmias, Daniel, et al.
Published: (2024)

Can Features for Phishing URL Detection Be Trusted Across Diverse Datasets? A Case Study with Explainable AI
by: Mia, Maraz, et al.
Published: (2024)

PhishGuard: A Multi-Layered Ensemble Model for Optimal Phishing Website Detection
by: Ovi, Md Sultanul Islam, et al.
Published: (2024)

A Machine Learning Driven Website Platform and Browser Extension for Real-time Scoring and Fraud Detection for Website Legitimacy Verification and Consumer Protection
by: Chy, Md Kamrul Hasan, et al.
Published: (2024)

Phishsense-1B: A Technical Perspective on an AI-Powered Phishing Detection Model
by: Blake, SE
Published: (2025)

PhishSnap: Image-Based Phishing Detection Using Perceptual Hashing
by: Minhaz, Md Abdul Ahad, et al.
Published: (2025)

PhishDebate: An LLM-Based Multi-Agent Framework for Phishing Website Detection
by: Li, Wenhao, et al.
Published: (2025)

Simple Perturbations Subvert Ethereum Phishing Transactions Detection: An Empirical Analysis
by: Alghureid, Ahod, et al.
Published: (2024)

Phishing Website Detection Using a Combined Model of ANN and LSTM
by: Farooq, Muhammad Shoaib, et al.
Published: (2024)

Detecting Financial Fraud with Hybrid Deep Learning: A Mix-of-Experts Approach to Sequential and Anomalous Patterns
by: Vallarino, Diego
Published: (2025)

A Survey of Malware Detection Using Deep Learning
by: Bensaoud, Ahmed, et al.
Published: (2024)

Position Paper: Think Globally, React Locally -- Bringing Real-time Reference-based Website Phishing Detection on macOS
by: Petrukha, Ivan, et al.
Published: (2024)

Adaptive Malware Detection using Sequential Feature Selection: A Dueling Double Deep Q-Network (D3QN) Framework for Intelligent Classification
by: Khan, Naseem, et al.
Published: (2025)

Detecting Compromised IoT Devices Using Autoencoders with Sequential Hypothesis Testing
by: Mainuddin, Md, et al.
Published: (2024)

Evaluating Large Language Models for Phishing Detection, Self-Consistency, Faithfulness, and Explainability
by: Kuikel, Shova, et al.
Published: (2025)

Phishing Detection in the Gen-AI Era: Quantized LLMs vs Classical Models
by: Thapa, Jikesh, et al.
Published: (2025)

An investigation into the performances of the Current state-of-the-art Naive Bayes, Non-Bayesian and Deep Learning Based Classifier for Phishing Detection: A Survey
by: Ige, Tosin, et al.
Published: (2024)

Small Language Models for Phishing Website Detection: Cost, Performance, and Privacy Trade-Offs
by: Goldenits, Georg, et al.
Published: (2025)

Towards Benchmark Datasets for Machine Learning Based Website Phishing Detection: An experimental study
by: Hannousse, Abdelhakim, et al.
Published: (2020)

An Explainable Transformer-based Model for Phishing Email Detection: A Large Language Model Approach
by: Uddin, Mohammad Amaz, et al.
Published: (2024)

RAPID: Robust APT Detection and Investigation Using Context-Aware Deep Learning
by: Amaru, Yonatan, et al.
Published: (2024)

SecureNet: A Comparative Study of DeBERTa and Large Language Models for Phishing Detection
by: Mahendru, Sakshi, et al.
Published: (2024)

KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detection
by: Li, Yuexin, et al.
Published: (2024)

A Sophisticated Framework for the Accurate Detection of Phishing Websites
by: Newaz, Asif, et al.
Published: (2024)

Attack and Defense of Deep Learning Models in the Field of Web Attack Detection
by: Shi, Lijia, et al.
Published: (2024)

Phishing Website Detection through Multi-Model Analysis of HTML Content
by: Çolhak, Furkan, et al.
Published: (2024)