Cryptography Comparative Analysis

A performance and security analysis of various cryptographic algorithms, including hashing, symmetric encryption, and asymmetric encryption. The study evaluates algorithm efficiency based on speed, resource usage, collision resistance, and brute-force resistance using practical experiments in Python.

Tech Stack

• Python
• matplotlib (Data Visualization)
• hashlib (Hashing)
• cryptography (Encryption)
• psutil (Resource Monitoring)
• csv (Data Storage)

Features

Hashing Algorithms Analysis

• Performance Testing: Measures hashing speed (MBps) for MD5, SHA-1, SHA-256, and BLAKE2.
• Resource Usage: CPU and memory consumption for each hashing algorithm.
• Collision Resistance: Tests for hash collisions in MD5, SHA-1, SHA-256, and BLAKE2.

Symmetric Encryption Analysis

• Algorithms Tested: AES, 3DES, and Blowfish.
• Encryption & Decryption Speed: Performance comparison in MBps.
• Resource Efficiency: CPU and memory usage monitoring.
• Brute-Force Resistance: Simulation of exhaustive key search for AES, 3DES, and Blowfish.

Asymmetric Encryption Analysis

• Algorithms Tested: RSA, ECC, and ElGamal.
• Performance Comparison: Encryption and decryption speeds.
• Ciphertext Size Growth: Analyzes ciphertext expansion for different plaintext sizes.
• Brute-Force Feasibility: Tests computational effort required for breaking RSA, ECC, and ElGamal encryption.

Data Visualization

• Graphical Analysis: Performance results plotted using Matplotlib.
• Hashing Speed & CPU Usage Charts.
• Encryption/Decryption Speed Comparisons.
• Ciphertext Size Growth Overhead Analysis.