Cybersecurity
Network Intrusion Detection System
Machine-learning anomaly detection over live network traffic
- Python
- Scapy
- XGBoost
- Kafka
- +2
Cybersecurity · Major Project
Classifies emails as phishing from their body text and headers
Overview
A text classifier that reads the email itself, not just its links: it combines TF-IDF and linguistic features from the body with header signals such as sender and reply-to mismatches and authentication results. Trained on public phishing and ham corpora, it explains each decision by surfacing the words and header facts that pushed it toward phishing.
What makes it stand up
Module breakdown
Splits raw emails into headers, body text and metadata.
Builds text vectors plus header-mismatch and tone signals.
Trains and compares models with precision and recall.
Shows the words and headers driving each classification.
Pastes an email and returns a phishing probability.
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Cybersecurity
Machine-learning anomaly detection over live network traffic