Phishing URL patterns study

The brief

Awareness training says "check the link", but which signs really give phishing away? Compare features of phishing and genuine URLs (length, symbols, domain age signals, HTTPS) with statistics, and show which ones differ most. Good looks like: correct tests with effect sizes, attention to features attackers can easily change, and charts for an awareness poster.

What you will build

1. Explore URL features for phishing and genuine sites
2. Compare distributions with appropriate tests
3. Report effect sizes, not only p-values
4. Discuss which signs attackers can fake
5. Design an awareness poster from the findings

Free, open data to build it with

• PhiUSIIL phishing URL dataset ↗ UCI Machine Learning Repository

Check each dataset's licence before you publish your work. Your mentor gives your team its own version of the brief (data, scope or region), so every team's project is its own.