Scalability Dataset

Description

Scalability_M1.csv - Scalability_M50.csv : A partial dataset containing evaluation metrics for 25 image samples from a single folder (M1 - M50) across five different resolutions (800x600 to 4K). Scability_M1_M50_2.csv: The comprehensive, combined dataset containing all 1,250 samples aggregated from 50 folders (M1 to M50). This is the main data source used to generate the $O(M \times N)$ time complexity graph.

Steps to reproduce

1. Configure: Set the target directory and specific folder (e.g., "M1") in your evaluation Python script. 2. Execute: Run the script. It will automatically process the images (encryption, embedding, and attacks), record all performance metrics (Time, RAM, Entropy, etc.), and save them into an individual file like Scalability_M1.csv. 3. Batch & Merge: To reproduce the large Scability_M1_M50_2.csv file, run the execution loop across all 50 folders sequentially, then use a Pandas script (pd.concat) to merge all 50 individual CSV files into one final dataset.

Institutions

• Universitas Ahmad Dahlan

  Yogyakarta, Yogyakarta

Categories

Licence