phishing risk intelligence
Year: 2026
Type: article
Abstract: This research was developed as part of the DBA 802 academic research work. The experimental results are based on the UCI Phishing Websites benchmark dataset and the completed machine-learning experiment documented in the accompanying paper. The reported metrics, SHAP analysis, figures, and risk-decision results correspond to the documented experimental run.
Author: tripuraneni, sukumar
Language: English
Topic: Spam and Phishing Detection
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7204134199
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