Major Project
Cybersecurity
Encrypted Storage and Steganography
Client-side AES encryption with hidden-payload image transport
- Python
- Django
- AES-256
- Steganography
- +1
₹3,599₹6,299
4.6/109 reviews
Cybersecurity · Capstone
Network Intrusion Detection System
Machine-learning anomaly detection over live network traffic
4-5 weeks build
Overview
A streaming IDS that captures packets, derives flow-level features, and flags intrusions with a trained ensemble model. Alerts stream into a live dashboard with severity scoring, and every detection links back to the exact flow that triggered it.
What makes it stand up
- 01Flow feature extraction matching the CIC-IDS schema
- 02Ensemble classifier with per-attack-class metrics
- 03Kafka pipeline for real-time scoring at line rate
- 04Grafana dashboard with severity and MITRE mapping
- 05Replayable PCAP attack scenarios for your demo
Module breakdown
- 01
Capture
Live sniffing and PCAP replay with flow assembly.
- 02
Feature engineering
Statistical, timing and protocol features.
- 03
Detection
Trained ensemble plus an unsupervised anomaly fallback.
- 04
Alerting
Severity scoring, deduplication and notification hooks.
- 05
Dashboard
Live traffic, alert timeline and drill-down views.
After this, you will be able to
- Compare signature-based and anomaly-based detection
- Justify your handling of class imbalance
- Run a live attack demo safely on a lab network
Technology stack
- Python
- Scapy
- XGBoost
- Kafka
- Grafana
- Docker
- Level
- Capstone
- Domain
- Cybersecurity
- Build time
- 4-5 weeks
- Difficulty
- Rating
- 4.9 / 5 · 97
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