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
Encrypted Storage and Steganography
Client-side AES encryption with hidden-payload image transport
2-3 weeks build
Overview
Files are encrypted in the browser before upload so the server never sees plaintext, and a second channel hides small payloads inside cover images using least-significant-bit steganography, with a full capacity and detectability analysis.
What makes it stand up
- 01Client-side AES-256-GCM with PBKDF2 key derivation
- 02Zero-knowledge server design with a documented threat model
- 03LSB steganography with capacity and PSNR analysis
- 04Secure sharing links with expiry and download limits
- 05Steganalysis section showing detection limits
Module breakdown
- 01
Cryptography
Key derivation, encryption and integrity tags.
- 02
Storage
Chunked upload, resumability and metadata.
- 03
Steganography
Embed, extract and quality measurement.
- 04
Sharing
Expiring links, access logs and revocation.
- 05
Analysis
PSNR, SSIM and chi-square detectability tests.
After this, you will be able to
- Explain your threat model precisely
- Compare cryptography and steganography as goals
- Present measured image-quality trade-offs
Technology stack
- Python
- Django
- AES-256
- Steganography
- React
- Level
- Major Project
- Domain
- Cybersecurity
- Build time
- 2-3 weeks
- Difficulty
- Rating
- 4.6 / 5 · 109
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