Iowa State University Digital Repository
metadata only
AI/ML-Powered Phishing Email Detection System: A Web App & Chrome Extension Approach
artificial-intelligence-and-roboticscomputer-and-systems-architecturecomputer-engineeringcomputer-sciencescybersecurityinformation-securityother-computer-engineeringphysical-sciences-and-mathematics
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- SENTINEL_SOC: An AI-Powered Backend Framework for Multi-Vector Phishing Detection#280609
- Identifying AI Web Scrapers Using Canary Tokens#180573
- CompPhish: A comprehensive dataset for diversified phishing detection.#1001054
- A Gmail-Based Phishing Detection Prototype for Nigerian Fintech Emails Using Sender Checks and BiLSTM Classification#1064849
- Comparison of the Performance of Machine Learning Classification Algorithms on Phishing URL Detection#436371
Record · ID 326478
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive