/steganalysis

Detection of LSB Matching Steganography in Greyscale Images - Machine Learning Nanodegree Capstone Project

Primary LanguageJupyter Notebook

Machine Learning Engineer Nanodegree

Steganalysis of LSB Matching in Greyscale Images - Capstone Project

Software Requirements

This project uses both Python 2 and Python 3. Python 2 is used in the 'Image Preprocessing.ipynb' notebook. All other python files use Python 3. I have used the Anaconda distribution of python for development. It includes libraries numpy, scipy, pandas, sklearn and matplotlib used in this project. The additional libraries used are seaborn, pillow and pywt. All of the mentioned libraries can be installed using 'pip install library_name' or 'conda install library_name'.

Dataset Details

I have used the BOSSbase dataset as my base dataset. It is available for download at:

http://dde.binghamton.edu/download/ImageDB/BOSSbase_1.01.zip

I have also included samples for both the original images in the BOSSbase dataset as well as the images after performing LSB matching. The steg images have been generated using the tool available at https://github.com/daniellerch/aletheia. Use the following command to generate the steg images:

$ python aletheia.py lsbm-sim bossbase 0.40 bossbase_lsb