Passwrod Cracking Dataset and Results

This archive contains the datasets and experimental results used to evaluate password security enhancement methods proposed in the study.

1. Password Datasets

The dataset consists of two primary groups of plaintext passwords:

• Set A (Longer Length, Lower Complexity)
  Contains passwords with relatively longer character lengths but simpler composition patterns (e.g., limited variation of character types).
• Set B (Shorter Length, Higher Complexity)
  Contains shorter passwords with more complex combinations of characters, including uppercase, lowercase, digits, symbols, and extended character sets (ECS).

Both sets are constructed based on 16 predefined password patterns, including 15 commonly used patterns and one additional pattern incorporating Extended Character Sets (ECS).

Additionally, visual representations (image datasets) are provided to illustrate character distribution patterns and entropy differences across methods.

2. Password Transformation Methods

Each plaintext password is processed using three different approaches:

• Baseline Method
  • Pre-Hash Coding (PHC)
• Proposed Methods
  • Model 1 (M1): Full-range character remapping
  • Model 2 (M2): Controlled mapping with constrained ECS distribution

These methods transform the original passwords into enhanced versions prior to hashing.

3. Hashed Password Datasets

All transformed passwords (PHC, M1, and M2) are further processed using a hashing algorithm to produce hashed password datasets, simulating real-world password storage mechanisms.

4. Brute-force Evaluation Results

The hashed passwords are subjected to brute-force attacks to evaluate security performance. The archive includes:

• Cracking time for each password instance
• Attack success/failure status
• Comparative results across PHC, M1, and M2
• Experiments conducted under:
  • Set A (PCS-based patterns)
  • Set B (Full character space including ECS)

5. Purpose of the Dataset

This dataset is designed to support reproducibility and further research on:

• Password security enhancement techniques
• Character distribution analysis
• Entropy vs. practical cracking resistance
• Lightweight authentication mechanisms for IoT and consumer devices