Web Phishing Net (WPN): A scalable machine learning approach for real-time phishing campaign detection
Fuente:
arXiv
Saved in:
| Main Authors: | Zia, Muhammad Fahad, Kalidass, Sri Harish |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Enhance the machine learning algorithm performance in phishing detection with keyword features
by: Yang, Zijiang
Published: (2025)
by: Yang, Zijiang
Published: (2025)
Comprehensive evaluation of Mal-API-2019 dataset by machine learning in malware detection
by: Li, Zhenglin, et al.
Published: (2024)
by: Li, Zhenglin, et al.
Published: (2024)
NoPhish: Efficient Chrome Extension for Phishing Detection Using Machine Learning Techniques
by: Thaqi, Leand, et al.
Published: (2024)
by: Thaqi, Leand, et al.
Published: (2024)
PhreshPhish: A Real-World, High-Quality, Large-Scale Phishing Website Dataset and Benchmark
by: Dalton, Thomas, et al.
Published: (2025)
by: Dalton, Thomas, et al.
Published: (2025)
Detecting new obfuscated malware variants: A lightweight and interpretable machine learning approach
by: Madamidola, Oladipo A., et al.
Published: (2024)
by: Madamidola, Oladipo A., et al.
Published: (2024)
Phishing the Phishers with SpecularNet: Hierarchical Graph Autoencoding for Reference-Free Web Phishing Detection
by: Song, Tailai, et al.
Published: (2026)
by: Song, Tailai, et al.
Published: (2026)
In-context learning for the classification of manipulation techniques in phishing emails
by: Dalmiere, Antony, et al.
Published: (2025)
by: Dalmiere, Antony, et al.
Published: (2025)
Explainable Transformer-Based Email Phishing Classification with Adversarial Robustness
by: P, Sajad U
Published: (2025)
by: P, Sajad U
Published: (2025)
Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features
by: Faisal, Aseer Al
Published: (2025)
by: Faisal, Aseer Al
Published: (2025)
Evaluating Large Language Models for Phishing Detection, Self-Consistency, Faithfulness, and Explainability
by: Kuikel, Shova, et al.
Published: (2025)
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)
by: Thapa, Jikesh, et al.
Published: (2025)
CST-AFNet: A dual attention-based deep learning framework for intrusion detection in IoT networks
by: Ishtiaq, Waqas, et al.
Published: (2025)
by: Ishtiaq, Waqas, et al.
Published: (2025)
An Explainable Transformer-based Model for Phishing Email Detection: A Large Language Model Approach
by: Uddin, Mohammad Amaz, et al.
Published: (2024)
by: Uddin, Mohammad Amaz, et al.
Published: (2024)
Fake detection in imbalance dataset by Semi-supervised learning with GAN
by: Bordbar, Jinus, et al.
Published: (2022)
by: Bordbar, Jinus, et al.
Published: (2022)
KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detection
by: Li, Yuexin, et al.
Published: (2024)
by: Li, Yuexin, et al.
Published: (2024)
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)
by: Ige, Tosin, et al.
Published: (2024)
A GAN-based data poisoning framework against anomaly detection in vertical federated learning
by: Chen, Xiaolin, et al.
Published: (2024)
by: Chen, Xiaolin, et al.
Published: (2024)
PhishNet: A Phishing Website Detection Tool using XGBoost
by: Kumar, Prashant, et al.
Published: (2024)
by: Kumar, Prashant, et al.
Published: (2024)
Every Character Counts: From Vulnerability to Defense in Phishing Detection
by: Chiper, Maria, et al.
Published: (2025)
by: Chiper, Maria, et al.
Published: (2025)
WebSP-Eval: Evaluating Web Agents on Website Security and Privacy Tasks
by: Ramesh, Guruprasad Viswanathan, et al.
Published: (2026)
by: Ramesh, Guruprasad Viswanathan, et al.
Published: (2026)
Teach LLMs to Phish: Stealing Private Information from Language Models
by: Panda, Ashwinee, et al.
Published: (2024)
by: Panda, Ashwinee, et al.
Published: (2024)
Throttling Web Agents Using Reasoning Gates
by: Kumar, Abhinav, et al.
Published: (2025)
by: Kumar, Abhinav, et al.
Published: (2025)
Verifiable evaluations of machine learning models using zkSNARKs
by: South, Tobin, et al.
Published: (2024)
by: South, Tobin, et al.
Published: (2024)
WAREX: Web Agent Reliability Evaluation on Existing Benchmarks
by: Kara, Su, et al.
Published: (2025)
by: Kara, Su, et al.
Published: (2025)
Quantum Machine Learning for Cybersecurity: A Taxonomy and Future Directions
by: Sai, Siva, et al.
Published: (2025)
by: Sai, Siva, et al.
Published: (2025)
Maximize margins for robust splicing detection
by: de Kergunic, Julien Simon, et al.
Published: (2025)
by: de Kergunic, Julien Simon, et al.
Published: (2025)
Training quantum machine learning models on cloud without uploading the data
by: He, Guang Ping
Published: (2024)
by: He, Guang Ping
Published: (2024)
eyeballvul: a future-proof benchmark for vulnerability detection in the wild
by: Chauvin, Timothee
Published: (2024)
by: Chauvin, Timothee
Published: (2024)
TempoNet: Learning Realistic Communication and Timing Patterns for Network Traffic Simulation
by: Moore, Kristen, et al.
Published: (2026)
by: Moore, Kristen, et al.
Published: (2026)
SafeBench-Seq: A Homology-Clustered, CPU-Only Baseline for Protein Hazard Screening with Physicochemical/Composition Features and Cluster-Aware Confidence Intervals
by: Khan, Muhammad Haris
Published: (2025)
by: Khan, Muhammad Haris
Published: (2025)
Unsafe LLM-Based Search: Quantitative Analysis and Mitigation of Safety Risks in AI Web Search
by: Luo, Zeren, et al.
Published: (2025)
by: Luo, Zeren, et al.
Published: (2025)
Beyond the Request: Harnessing HTTP Response Headers for Cross-Browser Web Tracker Classification in an Imbalanced Setting
by: Rieder, Wolf, et al.
Published: (2024)
by: Rieder, Wolf, et al.
Published: (2024)
Improving IoT Intrusion Detection Through SMOTE-Based Oversampling and Extended Multi-Model Evaluation on Side-Channel Power Data
by: Shahzad, Muhammad Khuram, et al.
Published: (2026)
by: Shahzad, Muhammad Khuram, et al.
Published: (2026)
Revolutionizing Encrypted Traffic Classification with MH-Net: A Multi-View Heterogeneous Graph Model
by: Zhang, Haozhen, et al.
Published: (2025)
by: Zhang, Haozhen, et al.
Published: (2025)
CyberNFTs: Conceptualizing a decentralized and reward-driven intrusion detection system with ML
by: Selimi, Synim, et al.
Published: (2024)
by: Selimi, Synim, et al.
Published: (2024)
AutoGraphAD: Unsupervised network anomaly detection using Variational Graph Autoencoders
by: Anyfantis, Georgios, et al.
Published: (2025)
by: Anyfantis, Georgios, et al.
Published: (2025)
Random Forest Stratified K-Fold Cross Validation on SYN DoS Attack SD-IoV
by: Zamrai, Muhammad Arif Hakimi, et al.
Published: (2025)
by: Zamrai, Muhammad Arif Hakimi, et al.
Published: (2025)
PhishLang: A Real-Time, Fully Client-Side Phishing Detection Framework Using MobileBERT
by: Roy, Sayak Saha, et al.
Published: (2024)
by: Roy, Sayak Saha, et al.
Published: (2024)
Analysis and prevention of AI-based phishing email attacks
by: Eze, Chibuike Samuel, et al.
Published: (2024)
by: Eze, Chibuike Samuel, et al.
Published: (2024)
Generalist++: A Meta-learning Framework for Mitigating Trade-off in Adversarial Training
by: Wang, Yisen, et al.
Published: (2025)
by: Wang, Yisen, et al.
Published: (2025)
Similar Items
-
Enhance the machine learning algorithm performance in phishing detection with keyword features
by: Yang, Zijiang
Published: (2025) -
Comprehensive evaluation of Mal-API-2019 dataset by machine learning in malware detection
by: Li, Zhenglin, et al.
Published: (2024) -
NoPhish: Efficient Chrome Extension for Phishing Detection Using Machine Learning Techniques
by: Thaqi, Leand, et al.
Published: (2024) -
PhreshPhish: A Real-World, High-Quality, Large-Scale Phishing Website Dataset and Benchmark
by: Dalton, Thomas, et al.
Published: (2025) -
Detecting new obfuscated malware variants: A lightweight and interpretable machine learning approach
by: Madamidola, Oladipo A., et al.
Published: (2024)