View Proposal

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Proposer

Zi Hau Chin

Title

Explainable Detection of Phishing Websites Using URL and Page-Level Features

Goal

Classify websites as phishing or legitimate and explain the URL and webpage characteristics contributing to the decision.

Description

A browser plugin for automated detection and prevention. -Does combining URL and page-level features outperform URL-only detection? -Do explanations improve users’ phishing decisions? -How well does the model generalise to newer domains? -How robust is it to common phishing evasion techniques?

Resources

PhiUSIIL UCI Dataset, PhiUSIIL on Mendeley Data, PhiUSIIL Data-Mining Project, Practical PhiUSIIL Detection Experiments

Background

Python, machine learning, web technologies, basic cybersecurity and phishing concepts, explainable AI, feature extraction and classification

Url

Difficulty Level

Moderate

Ethical Approval

Full

Number Of Students

1

Supervisor

Zi Hau Chin

Keywords

phishing detection, malicious url, explainable ai, url lexical features, html features, domain impersonation, browser security, adversarial evasion

Degrees

Bachelor of Science in Computing Science