WebbWe describe version 2.0 of our benchmarking framework, PhishBench. With the addition of the ability to dynamically load features, metrics, and classifiers, our new and improved framework allows researchers to rapidly evaluate new features and methods for machine-learning based phishing detection. WebbPhishBench is a extendable framework for benchmarking phishing detection systems. Using PhishBench, researchers can easily evaluate new features and classification … phishbench.feature_extraction ¶ This module handles feature extraction. It contai… phishbench.classification — PhishBench 2.0.2 documentation phishbench.classif… phishbench.input — PhishBench 2.0.2 documentation phishbench.input phishben… The PhishBench Configuration File is an ini file defined according to the Python [C… phishbench.evaluation ¶. The evaluation module evaluates classifiers against a te…

Python Module Index — PhishBench 2.0.2 documentation

WebbWe describe version 2.0 of our benchmarking framework, PhishBench. With the addition of the ability to dynamically load features, metrics, and classifiers, our new and improved … WebbPhishBench 2.0. Evaluate single-feature performance with PhishBench 2.0. Results: Objective 1 • Spellcheck ratio feature • Statistically different between phish and legit emails (p-value: 1.512e-22) • Random Forest identifies … tsf601-c

PhishBench 2.0: A Versatile and Extendable …

WebbPhishBench 2.0: A Versatile and Extendable Benchmarking Framework for Phishing. We describe version 2.0 of our benchmarking framework, PhishBench. With the addition of … WebbPhishBench 2.0: A Versatile and Extendable Benchmarking Framework for Phishing Victor Zeng (University of Houston); Xin Zhou (University of Houston); Shahryar Baki (University of Houston); Rakesh Verma (University of Houston) tsf60adr