Cryptography Benchmark

Benchmarking study of AES, RSA and SHA‑256 across multiple file sizes and scenarios.
We measure encryption, decryption and hashing performance, analysing both speed and stability (standard deviation).

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✨ Project Highlights

• Algorithms: AES (symmetric), RSA (asymmetric), SHA‑256 (hash).
• Scenarios: single file repeated N times vs N different files.
• Sizes: from a few bytes up to MB scale (log‑log comparisons).
• Metrics: mean execution time (µs) and standard deviation (stability).
• Deliverables: clean notebook, figures (in images/) and report.

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📂 Repository Structure

.
├── data/                          # Test inputs (optional)
├── images/                        # All generated figures (1.png … 15.png)
│   ├── 10.png   # RSA encryption vs decryption (log‑log)
│   ├── 11.png   # RSA standard deviation (enc/dec)
│   ├── 12.png   # SHA‑256 standard deviation (hashing)
│   ├── 13.png   # AES standard deviation (enc/dec)
│   ├── 14.png   # AES vs RSA encryption (log‑log)
│   ├── 15.png   # AES vs SHA‑256 encryption (log‑log)
│   └── …        # other figures (1–9)
├── notebooks/
│   └── cryptography_benchmark.ipynb   # Main notebook (code & analysis)
├── reports/
│   └── cryptography_report.pdf        # Final project report (optional)
├── requirements.txt                   # Python dependencies
├── LICENSE                            # MIT License
└── README.md                          # This file

ℹ️ Important: Image links below use the exact filenames in your repo (images/10.png, images/11.png, …).
If an image doesn’t render on GitHub, check that the filename and extension match exactly (case‑sensitive).

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📊 Visualizations

Standard Deviation Analysis

• SHA‑256 hashing stability
  

• RSA standard deviation (encryption & decryption)
  

• AES Encryption vs Decryption Times (log‑log)
  

Performance Comparisons

• AES vs RSA Encryption (log‑log)
  

• AES vs SHA-256 Encryption (log‑log)
  

• RSA Encryption vs Decryption Times (log‑log)
  

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▶️ How to Run

1. Install Python 3.11+.
2. (Optional) Create a virtual environment:

   python -m venv .venv
   source .venv/bin/activate       # macOS/Linux
   .venv\Scripts\activate        # Windows

3. Install dependencies:

   pip install -r requirements.txt

4. Launch the notebook:

   jupyter notebook notebooks/cryptography_benchmark.ipynb

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🔧 Dependencies

• numpy
• matplotlib
• timeit
• jupyter
• ipykernel

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👩‍💻 Author

• Ana Sofia Quintero
• Liliana Silva
• Catarina Abrantes

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📄 License

Licensed under the MIT License — see LICENSE for details.