Evaluating Human and Machine Confidence in Phishing Email Detection: A Comparative Study
Evaluating Human and Machine Confidence in Phishing Email Detection: A Comparative Study explores A study on how humans and machine learning models compare in detecting phishing emails.. Commercial viability score: 3/10 in Cybersecurity.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $10K - $14K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Prior WorkEroding the Truth-Default: A Causal Analysis of Human Susceptibility to Foundation Model Hallucinations and Disinformation in the WildViability: 3.0
- Higher ViabilityCIC-Trap4Phish: A Unified Multi-Format Dataset for Phishing and Quishing Attachment DetectionViability: 5.0
- Higher ViabilityPhishing the Phishers with SpecularNet: Hierarchical Graph Autoencoding for Reference-Free Web Phishing DetectionViability: 8.0
- Higher ViabilityMultilingual Financial Fraud Detection Using Machine Learning and Transformer Models: A Bangla-English StudyViability: 5.0