Capstone
Cybersecurity
Network Intrusion Detection System
Machine-learning anomaly detection over live network traffic
- Python
- Scapy
- XGBoost
- Kafka
- +2
₹5,499₹9,499
4.9/97 reviews
Cybersecurity · Major Project
Malware Detection with Machine Learning
Classifies Windows executables as benign or malicious from static features
3-4 weeks build
Overview
Trains a gradient-boosted classifier on the public EMBER dataset, which describes Windows PE files through pre-extracted static features such as header fields, imports, section entropy and byte histograms. No live malware is executed or distributed. A small web app extracts the same features from an uploaded file and returns a verdict with the features that drove it.
What makes it stand up
- 01Built on EMBER's published static feature vectors, no live samples needed
- 02LightGBM model compared against a random forest baseline
- 03ROC curve, confusion matrix and false-positive analysis in the report
- 04Feature-importance view explaining what drove each verdict
- 05Upload-and-scan web interface for benign test executables
Module breakdown
- 01
Dataset
Loads EMBER vectors and builds train and test splits by date.
- 02
Feature study
Explores imports, section entropy and header fields by class.
- 03
Model
Gradient boosting with tuned depth, learning rate and leaves.
- 04
Evaluation
Measures detection rate at fixed false-positive thresholds.
- 05
Scanner app
Extracts PE features from an upload and shows the verdict.
After this, you will be able to
- Explain what static PE features reveal and what they miss
- Defend why false positives matter more than raw accuracy here
- Demo a verdict with its top contributing features
Technology stack
- Python
- LightGBM
- scikit-learn
- Pandas
- Flask
- Level
- Major Project
- Domain
- Cybersecurity
- Build time
- 3-4 weeks
- Difficulty
You receive
- Complete, commented source code
- 60-90 page project report (IEEE format)
- Editable presentation deck
- Architecture, ER and UML diagrams
- Local setup and deployment guide
- Sample dataset or seed data
- Viva question bank with answers
- One 45-minute walkthrough call
- 30 days of doubt-clearing support