Saved in:
| Main Authors: | Dora, Nikhil Kumar, Tetarave, Sumit Kumar, Sahay, Rishikesh, Singh, Madhusudan, Li, Xiaoqing |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.17891 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Policy-Guided Threat Hunting: An LLM enabled Framework with Splunk SOC Triage
by: Sahay, Rishikesh, et al.
Published: (2026)
by: Sahay, Rishikesh, et al.
Published: (2026)
PhishIntel: Toward Practical Deployment of Reference-Based Phishing Detection
by: Li, Yuexin, et al.
Published: (2024)
by: Li, Yuexin, et al.
Published: (2024)
EXPLICATE: Enhancing Phishing Detection through Explainable AI and LLM-Powered Interpretability
by: Lim, Bryan, et al.
Published: (2025)
by: Lim, Bryan, et al.
Published: (2025)
Towards Benchmark Datasets for Machine Learning Based Website Phishing Detection: An experimental study
by: Hannousse, Abdelhakim, et al.
Published: (2020)
by: Hannousse, Abdelhakim, et al.
Published: (2020)
Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector
by: Kulkarni, Aditya, et al.
Published: (2025)
by: Kulkarni, Aditya, et al.
Published: (2025)
PhishNet: A Phishing Website Detection Tool using XGBoost
by: Kumar, Prashant, et al.
Published: (2024)
by: Kumar, Prashant, et al.
Published: (2024)
PhishSSL: Self-Supervised Contrastive Learning for Phishing Website Detection
by: Li, Wenhao, et al.
Published: (2025)
by: Li, Wenhao, et al.
Published: (2025)
Machine Learning Driven Smishing Detection Framework for Mobile Security
by: Goel, Diksha, et al.
Published: (2024)
by: Goel, Diksha, et al.
Published: (2024)
Mitigating Bias in Machine Learning Models for Phishing Webpage Detection
by: Kulkarni, Aditya, et al.
Published: (2024)
by: Kulkarni, Aditya, et al.
Published: (2024)
Assessing Cyber Risks in Hydropower Systems Through HAZOP and Bow-Tie Analysis
by: Frempong-Kore, Kwabena Opoku, et al.
Published: (2026)
by: Frempong-Kore, Kwabena Opoku, et al.
Published: (2026)
Context-Aware Phishing Email Detection Using Machine Learning and NLP
by: Chakravorty, Amitabh, et al.
Published: (2026)
by: Chakravorty, Amitabh, et al.
Published: (2026)
MultiPhishGuard: An Explainable and Adaptive Multi-Agent LLM System for Phishing Email Detection
by: Xue, Yinuo, et al.
Published: (2025)
by: Xue, Yinuo, et al.
Published: (2025)
Governing AI-Assisted Security Operations: A Design Science Framework for Operational Decision Support
by: De La Cruz, Elyson A., et al.
Published: (2026)
by: De La Cruz, Elyson A., et al.
Published: (2026)
PhishGuard: A Convolutional Neural Network Based Model for Detecting Phishing URLs with Explainability Analysis
by: Islam, Md Robiul, et al.
Published: (2024)
by: Islam, Md Robiul, et al.
Published: (2024)
PhishAgent: A Robust Multimodal Agent for Phishing Webpage Detection
by: Cao, Tri, et al.
Published: (2024)
by: Cao, Tri, et al.
Published: (2024)
Interpretable Anomaly Detection in Encrypted Traffic Using SHAP with Machine Learning Models
by: Singh, Kalindi, et al.
Published: (2025)
by: Singh, Kalindi, et al.
Published: (2025)
PhishDebate: An LLM-Based Multi-Agent Framework for Phishing Website Detection
by: Li, Wenhao, et al.
Published: (2025)
by: Li, Wenhao, et al.
Published: (2025)
Can Features for Phishing URL Detection Be Trusted Across Diverse Datasets? A Case Study with Explainable AI
by: Mia, Maraz, et al.
Published: (2024)
by: Mia, Maraz, 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)
Phishing Detection in Ethereum via Temporal Graph Contrastive Learning
by: Wu, Cong, et al.
Published: (2026)
by: Wu, Cong, et al.
Published: (2026)
Efficient Phishing URL Detection Using Graph-based Machine Learning and Loopy Belief Propagation
by: Guo, Wenye, et al.
Published: (2025)
by: Guo, Wenye, et al.
Published: (2025)
CIC-Trap4Phish: A Unified Multi-Format Dataset for Phishing and Quishing Attachment Detection
by: Nejati, Fatemeh, et al.
Published: (2026)
by: Nejati, Fatemeh, et al.
Published: (2026)
MCP Guardian: A Security-First Layer for Safeguarding MCP-Based AI System
by: Kumar, Sonu, et al.
Published: (2025)
by: Kumar, Sonu, et al.
Published: (2025)
SolPhishHunter: Towards Detecting and Understanding Phishing on Solana
by: Li, Ziwei, et al.
Published: (2025)
by: Li, Ziwei, et al.
Published: (2025)
Smishing Dataset I: Phishing SMS Dataset from Smishtank.com
by: Timko, Daniel, et al.
Published: (2024)
by: Timko, Daniel, et al.
Published: (2024)
Evaluating The Explainability of State-of-the-Art Deep Learning-based Network Intrusion Detection Systems
by: Kumar, Ayush, et al.
Published: (2024)
by: Kumar, Ayush, et al.
Published: (2024)
PhishGuard: A Multi-Layered Ensemble Model for Optimal Phishing Website Detection
by: Ovi, Md Sultanul Islam, et al.
Published: (2024)
by: Ovi, Md Sultanul Islam, et al.
Published: (2024)
MCP-in-SoS: Risk assessment framework for open-source MCP servers
by: Kumar, Pratyay, et al.
Published: (2026)
by: Kumar, Pratyay, et al.
Published: (2026)
MemoPhishAgent: Memory-Augmented Multi-Modal LLM Agent for Phishing URL Detection
by: Chen, Xuan, et al.
Published: (2026)
by: Chen, Xuan, et al.
Published: (2026)
Phish-Blitz: Advancing Phishing Detection with Comprehensive Webpage Resource Collection and Visual Integrity Preservation
by: Hriday, Duddu, et al.
Published: (2025)
by: Hriday, Duddu, et al.
Published: (2025)
Comparative Analysis of Black-Box and White-Box Machine Learning Model in Phishing Detection
by: Fajar, Abdullah, et al.
Published: (2024)
by: Fajar, Abdullah, et al.
Published: (2024)
Detecting Phishing Sites Using ChatGPT
by: Koide, Takashi, et al.
Published: (2023)
by: Koide, Takashi, et al.
Published: (2023)
Automated Phishing Detection Using URLs and Webpages
by: Wang, Huilin, et al.
Published: (2024)
by: Wang, Huilin, et al.
Published: (2024)
E-PhishGen: Unlocking Novel Research in Phishing Email Detection
by: Pajola, Luca, et al.
Published: (2025)
by: Pajola, Luca, et al.
Published: (2025)
PhishSigma++: Malicious Email Detection with Typed Entity Relations
by: Shang, Shang, et al.
Published: (2026)
by: Shang, Shang, et al.
Published: (2026)
Jailbreaking Generative AI: Empowering Novices to Conduct Phishing Attacks
by: Mishra, Rina, et al.
Published: (2025)
by: Mishra, Rina, et al.
Published: (2025)
How Can We Effectively Use LLMs for Phishing Detection?: Evaluating the Effectiveness of Large Language Model-based Phishing Detection Models
by: Ji, Fujiao, et al.
Published: (2025)
by: Ji, Fujiao, et 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)
A Gradient-Optimized TSK Fuzzy Framework for Explainable Phishing Detection
by: Pentapalli, Lohith Srikanth, et al.
Published: (2025)
by: Pentapalli, Lohith Srikanth, et al.
Published: (2025)
Enhancing Phishing Detection in Financial Systems through NLP
by: Amirov, Novruz, et al.
Published: (2025)
by: Amirov, Novruz, et al.
Published: (2025)
Similar Items
-
Policy-Guided Threat Hunting: An LLM enabled Framework with Splunk SOC Triage
by: Sahay, Rishikesh, et al.
Published: (2026) -
PhishIntel: Toward Practical Deployment of Reference-Based Phishing Detection
by: Li, Yuexin, et al.
Published: (2024) -
EXPLICATE: Enhancing Phishing Detection through Explainable AI and LLM-Powered Interpretability
by: Lim, Bryan, et al.
Published: (2025) -
Towards Benchmark Datasets for Machine Learning Based Website Phishing Detection: An experimental study
by: Hannousse, Abdelhakim, et al.
Published: (2020) -
Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector
by: Kulkarni, Aditya, et al.
Published: (2025)