AI / Python
Wutong Defense Console
An AI-powered campus telecom fraud detection system combining risk portraits, rules, and machine learning.
Overview
A privacy-aware defense console for identifying telecom fraud patterns targeting students in Hong Kong.
Problem
Fraud signals are distributed across identity, exposure, behavior, and evolving attack patterns.
Solution
Combine a risk-triangle scorer, seven-rule engine, XGBoost, Isolation Forest, and human review.
Technology
Python, XGBoost, Isolation Forest, Streamlit, Differential Privacy
- Python
- XGBoost
- Isolation Forest
- Streamlit
Architecture
Feature engineering feeds risk portraits, rule-based classification, and hybrid ML detection modules.
Outcome
A system that reports 0.89 AUC in the project benchmark and supports explainable review flows.